The present disclosure relates to a monitoring system and a monitoring method.
Patent Document 1 describes a monitoring apparatus that obtains the position of an object in a monitoring area. The monitoring apparatus of Patent Document 1 includes an object detection unit, an imaging unit, an image processing unit, and a control unit. The object detection unit includes an antenna for transmitting and receiving electromagnetic waves having a predetermined beam width in a plurality of directions and detects the presence or absence of an object in the monitoring area from a reflected wave with respect to a transmitted wave and obtains an angle range in which the object exists. When the object detection unit detects an object, the control unit sets a range in the image corresponding to the angle range as an inspection area and controls a pan-tilt-zoom mechanism so that the inspection area is included in the image. The image processing unit specifies the angle at which the object exists by executing image processing in the inspection area in the image.
In Patent Document 1, the detection of an object in the monitoring area by the object detection unit triggers the setting of an inspection area by the imaging unit. Thus, if the object detection unit cannot detect an object existing in the monitoring area, problematically, an alarm cannot be activated to notify of the existence of the object. This leaves room for improvement with respect to Patent Document 1 in terms of, when one of the object detection unit and the imaging unit detects an object, the other can correctly detect the position of the object.
The present disclosure has been made in view of the above-described known circumstances, and an object is to improve the detection accuracy of an object existing in a monitoring area.
The present disclosure provides a monitoring system including a radar and at least one camera. The radar includes an antenna unit configured to transmit an electromagnetic wave to a first monitoring area and receive a reflected wave of the electromagnetic wave, a detection unit configured to execute detection processing to detect a presence or absence of an object in the first monitoring area on a basis of the reflected wave, and a control unit configured to generate detected object attribute information indicating an attribute of a detected object detected by the detection unit on a basis of a result of the detection processing and configured to generate radar position information indicating a position of the detected object on a basis of first installation information including an antenna installation position and an antenna direction and information of an antenna field of view. The at least one camera includes an imaging unit configured to image a second monitoring area at least partially overlapping the first monitoring area, and a processing unit configured to obtain imaging position information indicating a position of an imaged object included in a captured image of the second monitoring area on a basis of second installation information including an installation position of the imaging unit and an imaging direction of the imaging unit and information of a field of view of the imaging unit and obtain imaged object attribute information indicating an attribute of the imaged object on a basis of the captured image. The monitoring system includes a determination unit that executes determination processing to determine whether or not the detected object and the imaged object are an identical object on a basis of the radar position information and the imaging position information, and a notification control unit that causes a notification unit that executes notification processing to notify a user of notification information, and the notification information is, in a case where the detected object and the imaged object are an identical object, information in which a first identifier for identifying the detected object, the detected object attribute information, the captured image, and the imaged object attribute information at least are associated together, and is, in a case where the detected object and the imaged object are not an identical object, information based on at least one of the radar position information, the detected object attribute information, the imaging position information, or the imaged object attribute information.
The present disclosure also provides a monitoring method including: transmitting an electromagnetic wave to a first monitoring area and receiving a reflected wave of the electromagnetic wave; executing detection processing to detect a presence or absence of an object in the first monitoring area on a basis of the reflected wave; generating detected object attribute information indicating an attribute of a detected object detected by a detection unit that executes the detection processing on a basis of a result of the detection processing and generates radar position information indicating a position of the detected object on a basis of first installation information including an antenna installation position and an antenna direction and information of an antenna field of view; imaging, with an imaging unit, a second monitoring area at least partially overlapping the first monitoring area; obtaining imaging position information indicating a position of an imaged object included in a captured image of the second monitoring area on a basis of second installation information including an installation position of the imaging unit and an imaging direction of the imaging unit and information of a field of view of the imaging unit and obtaining imaged object attribute information indicating an attribute of the imaged object on a basis of the captured image; executing determination processing to determine whether or not the detected object and the imaged object are an identical object on a basis of the radar position information and the imaging position information; and causing a notification unit that executes notification processing to notify a user of notification information. In a case where the detected object and the imaged object are an identical object, the notification information is information in which a first identifier for identifying the detected object, the detected object attribute information, the captured image, and the imaged object attribute information at least are associated together. In a case where the detected object and the imaged object are not an identical object, the notification information is information based on at least one of the radar position information, the detected object attribute information, the imaging position information, or the imaged object attribute information.
According to the present disclosure, the detection accuracy of an object present in a monitoring area can be improved.
Hereinafter, embodiments that specifically disclose a monitoring system and a monitoring method according to the present disclosure will be described in detail with reference to the accompanying drawings as appropriate. However, unnecessary details may be omitted from the description. For example, a detailed description of a well-known matter or a redundant description relating to a substantially similar configuration may be omitted. This is to avoid unnecessary redundancy in the following description and to facilitate understanding by those skilled in the art. The accompanying drawings and the following description are provided to enable those skilled in the art to sufficiently understand the present disclosure and are not intended to limit the subject matter described in the claims.
The network NW may be a wired communication network (for example, a wired local area network (LAN) or a wired wide area network (WAN)). The network NW may be a wireless communication network (for example, a Bluetooth® network, a wireless LAN, a long term evolution (LTE) network, or a 5th generation mobile communication system (5G) network). Note that communication between the server 30 and the security robot 40 via the network NW is preferably wireless communication. The communication between the server 30 and the security guard terminal 50 via the network NW is preferably wireless communication.
The monitoring radar 10 transmits electromagnetic waves toward a first monitoring area AR1 (see
The server 30 corresponds to an information processing apparatus (a computer) that notifies a user terminal (for example, the security robot 40, the security guard terminal 50, or a monitor 70) of notification information, which is information the user terminal is to be notified of relating to a detected object and/or an imaged object.
The security robot 40 is communicatively connected to the server 30 via the network NW. The security robot 40 may include, for example, a camera, a speaker, lighting, and the like. The security robot 40 moves and threatens, warns, or performs a similar action targeting a detected object or an imaged object using sound or illumination light. The security robot 40 may image a detected object or an imaged object and transmit the captured image to the server 30. The security robot 40 corresponds to, for example, a multicopter type unmanned aircraft (a so-called drone), a robot that can autonomously move on the basis of a control signal, or the like.
The security guard terminal 50 is an information processing apparatus carried by a security guard and is communicatively connected to the server 30 via the network NW. A security guard terminal 50 is implemented by, for example, a portable information processing apparatus such as a tablet terminal or a smartphone. Note that the monitoring system 100 may include two or more security guard terminals 50.
Next, the internal configuration of the server 30 will be described. The server 30 is implemented by an information processing apparatus such as a personal computer (PC) and includes a server processor 31, a memory 32, a database 33, and a communication unit 34. The server 30 is electrically connected to an operation device 60 and the monitor 70. The database 33 may be installed in an information processing apparatus other than the server 30 or may be connected to the server 30 so as to be able to communicate data signals with the server 30.
The server processor 31 is an arithmetic apparatus such as a central processing unit (CPU), a graphical processing unit (GPU), or a field programmable gate array (FPGA) and functions as a controller that controls the overall operations of the server 30.
The memory 32 includes, for example, a random-access memory (RAM) and a read-only memory (ROM). The RAM is the working memory of the server processor 31 and temporarily stores data and information generated or obtained by the server processor 31. The ROM stores a program that defines the operations of the server processor 31 and stores control data. The memory 32 may further include a storage device such as a flash memory, a solid state drive (SSD), or a hard disk drive (HDD).
The database 33 is, for example, a storage device such as an HDD or an SSD and stores various types of information. Identification information (for example, serial number, ID, or the like) of the monitoring radar 10 and identification information (for example, serial number, ID, or the like) of the camera 20 may be registered (stored).
The communication unit 34 is a communication circuit that communicates data signals with the monitoring radar 10, the fixed camera 20A, the PTZ camera 20B, the security robot 40, and the security guard terminal 50 via the network NW.
The operation device 60 is an input device for inputting a data signal to the server 30 and corresponds to a portable information processing terminal or the like operated by a user (for example, a security guard carrying out their monitoring duties using the monitoring system 100; the same applies hereinafter). The monitor 70 corresponds to a display apparatus that displays the data signal output from the server 30. Note that when the operation device 60 is a touch panel, the operation device 60 and the monitor 70 may be integrally formed.
In the present embodiment, the server processor 31 (an example of a determination unit) executes determination processing to determine whether or not the detected object detected in the first monitoring area AR1 and the imaged object included in the camera image of the second monitoring area AR2 are an identical object.
In addition, in the present embodiment, the server processor 31 (an example of a notification information control unit) generates notification information for a user terminal (for example, the security robot 40, the security guard terminal 50, the monitor 70, or the like) and notifies the user terminal or the like of alarm activation via the communication unit 34.
Next, the monitoring radar 10 will be described with reference to
The radar processor 11 is implemented by, for example, a CPU, a GPU, or an FPGA and functions as a controller that controls the overall operations of the monitoring radar 10. The memory 12 includes a RAM and a ROM. The RAM is a work area used by the radar processor 11 for calculations and temporarily stores data or information generated or obtained by the radar processor 11. The ROM stores a program that defines the operations of the radar processor 11 and stores control data. The memory 12 may further include a storage device such as a flash memory, an SSD, or an HDD.
The radar processor 11 includes an AI processing unit 15 that executes processing using artificial intelligence (AI). The AI processing unit 15 includes an AI calculation processing unit 151 and a learning model memory 152. That is, the monitoring radar 10 can execute various types of processing using AI.
The AI calculation processing unit 151 loads a trained model from the learning model memory 152 and forms a neural network specialized in the processing of the loaded trained model. The learning model memory 152 is implemented by, for example, a flash memory and stores a trained model generated in advance by learning processing.
The trained model according to the present embodiment corresponds to, for example, a model for causing the AI to execute processing for determining the type of the detected object, specifically, whether the detected object is a person, a vehicle, or a two-wheeled vehicle, on the basis of the result of the detection processing. Note that other processing may be used including, for example, using a trained model that causes the AI to obtain the movement speed of the detected object on the basis of the result of the detection processing. The information relating to the type of the detected object is an example of detected object attribute information according to the present embodiment.
The detection unit 13 includes n (n being an integer equal to or greater than 1) radar ICs 131, . . . , 13n. In the following description, when it is not necessary to distinguish between the radar ICs 131, . . . , 13n, they may be referred to as “radar IC 13n”. The radar IC 13n is a communication circuit that controls, for example, emission of electromagnetic waves having wavelengths of from about 1 mm to 10 mm from a transmission antenna and reception of electromagnetic waves from a reception antenna, and can form beamforming of electromagnetic waves or reflected waves to a directed area (see description below) corresponding to its own radar IC. Different directed areas are set for the radar ICs 131, . . . , 13n, respectively. The directed area according to the present embodiment is, for example, a sector-shaped area centered on the radar installation position when the monitoring radar 10 is viewed from above (see
The antenna unit An includes n (n being an integer equal to or greater than 1) transmission antenna units ATx1, . . . , ATxn and n reception antenna units ARx1, . . . , ARxn. The antenna unit An includes n pairs of one transmission antenna unit and one reception antenna unit. Specifically, provided are a first pair including the transmission antenna unit ATx1 and the reception antenna unit ARx1, . . . , and an n-th pair including the transmission antenna unit ATxn and the reception antenna unit ARxn. The radar ICs are each provided so as to correspond to one of these pairs. That is, the radar IC 131 is connected to the transmission antenna unit ATx1 and the reception antenna unit ARx1 of the first pair. The radar IC 13n is connected to the transmission antenna unit ATxn and the reception antenna unit ARxn of the n-th pair. The transmission antenna units ATx1, . . . , ATxn and the reception antenna units ARx1, . . . , ARxn each include one antenna or a plurality of antennas.
The transmission antenna units ATx1, . . . , ATxn each convert analog signals from the corresponding radar ICs 131, . . . , 13n into electromagnetic waves and emit the electromagnetic waves.
Each of the reception antenna units ARx1, . . . , ARxn receives a reflected wave obtained by an electromagnetic wave emitted from a corresponding transmission antenna being reflected by an object. The reception antenna units ARx1, . . . , ARxn convert the received reflected waves into analog signals and send the analog signals to the corresponding radar ICs 131, . . . , 13n.
The communication unit 14 is a communication circuit that communicates data signals with the fixed camera 20A, the PTZ camera 20B, or the server 30.
As described above, with the monitoring radar 10, the radar processor 11 (an example of a determination unit) executes determination processing to determine whether or not the detected object detected in the first monitoring area AR1 and the imaged object included in the camera image of the second monitoring area AR2 are an identical object.
In addition, the radar processor 11 (an example of a notification information control unit) generates notification information for a user terminal (for example, the security robot 40, the security guard terminal 50, and the monitor 70).
The memory 12 may store information relating to the first monitoring area AR1 (see
Next, the configuration of the camera 20 will be described with reference to
The fixed camera 20A includes at least a camera processor 21A, a memory 22A, an imaging unit 23A, and a communication unit 24A. The fixed camera 20A corresponds to a camera, such as a box camera or a dome camera, whose angle of view cannot be changed after installation.
The camera processor 21A, for example, is a CPU, GPU, or FPGA and functions as a controller that controls the overall operation of the fixed camera 20A. The memory 22A includes a RAM and a ROM. The RAM is a work area used by the camera processor 21A for calculations and temporarily stores data or information generated or obtained by the camera processor 21A. The ROM stores a program that defines the operations of the camera processor 21A and stores control data.
The memory 22A may further include a storage device such as a flash memory, an SSD, or an HDD. The memory 22A stores information relating to the second monitoring area AR2 (see
The camera processor 21A includes the AI processing unit 25A that executes processing using AI. The AI processing unit 25A includes an AI calculation processing unit 251A and a learning model memory 252A. That is, the fixed camera 20A can execute various types of processing using AI.
The AI calculation processing unit 251A loads a trained model from the learning model memory 252A and forms a neural network specialized in the processing of the loaded trained model. The learning model memory 252A is implemented by, for example, a flash memory and stores a trained model generated in advance by learning processing. The trained model of the learning model memory 252A may be, for example, a model for detecting an object in image data captured by the imaging unit 23A. In addition, the trained model of the learning model memory 252A may be a model that performs attribute classification for extracting imaged object attribute information relating to an object in image data captured by the imaging unit 23A.
The imaging unit 23A images a subject (for example, imaged objects such as persons and vehicles; the same applying hereinafter) in the second monitoring area AR2 (see
The communication unit 24A is a communication circuit that communicates data signals with the monitoring radar 10, the PTZ camera 20B, or the server 30.
Next, the configuration of the PTZ camera 20B will be described with reference to
The PTZ camera 20B includes at least a camera processor 21B, a memory 22B, an imaging unit 23B, a communication unit 24B, and a camera drive unit 26B. The PTZ camera 20B corresponds to a camera having a pan-tilt-zoom mechanism and that can change the angle of view after installation.
The camera processor 21B, for example, is a CPU, GPU, or FPGA. The camera processor 21B functions as a controller that controls the overall operation of the PTZ camera 20B. The memory 22B includes a RAM and a ROM. The RAM is a work area used by the camera processor 21B for calculations and temporarily stores data or information generated or obtained by the camera processor 21B. The ROM stores a program that defines the operations of the camera processor 21B and stores control data.
The memory 22B may further include a storage device such as a flash memory, an SSD, or an HDD. The memory 22B stores information relating to the second monitoring area AR2 (see
The camera processor 21B includes an AI processing unit 25B that can execute predetermined signal processing using AI. The AI processing unit 25B includes an AI calculation processing unit 251B and a learning model memory 252B. That is, the PTZ camera 20B can execute various types of processing using AI.
The AI calculation processing unit 251B loads a trained model from the learning model memory 252B and forms a neural network specialized in the processing of the loaded trained model. The learning model memory 252B is implemented by, for example, a flash memory and stores a trained model generated in advance by learning processing. The trained model of the learning model memory 252B may be, for example, a model for detecting an object in image data captured by the imaging unit 23B. In addition, the trained model of the learning model memory 252B may be a model that performs attribute classification for extracting imaged object attribute information relating to an object in image data captured by the imaging unit 23B.
The imaging unit 23B images a subject (for example, detected objects such as persons and vehicles, the same applying hereinafter) in the second monitoring area AR2 (see
The communication unit 24B is a communication circuit that communicates data signals with the monitoring radar 10, the fixed camera 20A, or the server 30.
The camera drive unit 26B includes a rotary motor 261 and a zoom motor 262. The rotary motor 261 is a drive unit for performing pan rotation and/or tilt rotation of the housing of the PTZ camera 20B. The rotary motor 261 performs pan rotation and tilt rotation by being driven in accordance with the motor position calculated by the camera processor 21B. The zoom motor 262 is a drive unit for driving a zoom lens included in the imaging unit 23. The zoom motor 262 is driven in accordance with the motor position calculated by the camera processor 21B to change the optical magnification of the lens included in the imaging unit 23. In this manner, the camera drive unit 26B controls pan rotation and tilt rotation of the housing of the PTZ camera 20B and controls zoom processing using the zoom lens included in imaging unit 23B.
The camera processor 21B calculates a target position of the rotary motor 261 for the imaging unit 23 to image a detected object at a first position (for example, a position at which a moving object is detected) indicated by the radar position information detected by the monitoring radar 10. At this time, the camera processor 21B may calculate, together with the target position of the rotary motor 261, a target position of the zoom motor 262 suitable for the imaging unit 23B to image the detected object at the first position. Specifically, the camera processor 21B calculates the target position of the rotary motor 261 on the basis of the relationship between the position (for example, the current position) of rotary motor 261 held by the PTZ camera 20B and the imaging range (for example, the second monitoring area AR2) in real space and second installation information (for example, the camera installation position and the camera imaging direction of the PTZ camera 20B). Also, the camera processor 21B calculates the target position of zoom motor 262 on the basis of the relationship between the position (for example, the current position) of zoom motor 262 held by the PTZ camera 20B and the imaging range (for example, the second monitoring area AR2) in real space and second installation information (for example, the camera installation position and the camera imaging direction of the PTZ camera 20B).
Next, a correspondence relationship between a radar map RMP1 and a camera image IMG1 according to the present embodiment will be described with reference to
The camera image IMG1 is an image captured by the camera 20.
The radar map RMP1 indicates the detection result of the monitoring radar 10 in the first monitoring area AR1 with the installation position of the monitoring radar 10 set as an origin Orcs of the radar coordinate system RCS. The radar map RMP1 corresponds to a detection result of the monitoring radar 10 represented in a visually comprehensible manner.
Here, an outline of the coordinate conversion between the radar coordinate system RCS, the camera coordinate system CCS, and the image coordinate system ICS according to the present embodiment will be described with reference to
In Equation (1), [Xc, Yc, Zc] are camera coordinates in the camera coordinate system CCS. That is, [Xc, Yc, Zc] corresponds to a position in the camera coordinate system CCS as viewed from the origin of the camera coordinate system CCS (that is, the camera installation position of the camera 20). [Xw, Yw, Zw] are radar coordinates in the radar coordinate system RCS. That is, [Xw, Yw, Zw] corresponds to a position in the radar coordinate system RCS as viewed from the origin of the radar coordinate system RCS (that is, the radar installation position of the monitoring radar 10). According to Equation (1), [Xc, Yc, Zc] corresponds to the sum of the product of [Xw, Yw, Zw] and the external parameters indicating the rotation matrix for rotating [Xw, Yw, Zw] indicating the radar coordinates in the radar coordinate system RCS and the external parameters [t1, t2, t3] indicating the movement (translation) of the origin of the radar coordinate system RCS to the origin of the camera coordinate system CCS. As seen in Equation (1), an arbitrary position (coordinates) in the radar coordinate system RCS can be converted into a position (coordinates) in the camera coordinate system CCS. In addition, an arbitrary position (coordinates) in the camera coordinate system CCS can be converted into a position (coordinates) in the radar coordinate system RCS by a modification in which an inverse matrix of the rotation matrix of Equation (1) is found.
Next, a schematic example of coordinate conversion between the camera coordinate system CCS and the image coordinate system ICS will be described with reference to
As described above, the image coordinate system ICS is a two-dimensional coordinate system. In this description, it is assumed that the image coordinate system ICS is defined by an image plane projected from the origin of the camera coordinate system CCS (that is, the camera installation position of the camera 20) to a position at the depth s. At this time, a position (u, v) in the image coordinate system ICS as viewed from the origin Oics (see
As described above with reference to
Returning to
The monitoring radar 10 transmits, to the server 30, the coordinates of person Ps1 and the coordinates of vehicles Vc1 and Vc2 in the image coordinate system ICS after conversion processing from the radar coordinate system RCS to the image coordinate system ICS. The radar processor 11 (monitoring radar 10) may superimpose information (frame Fp1 or the like) indicating the person Ps1 on the coordinates of the person Ps1 in the image coordinate system ICS (see
Data of the three-dimensional radar map RMP1 corresponding to the radar coordinate system RCS may be stored in the camera 20, and the camera 20 may convert the coordinates (x1, y1, z1) in the radar coordinate system RCS into the coordinates (u1, v1) in the image coordinate system ICS using Equations (1) and (2).
Next, the correspondence relationship between the radar map RMP1 and the camera image IMG1 in the camera 20 will be described. The camera 20 executes processing to convert the coordinates of the person Ps1 and the vehicles Vc1 and Vc2 in the image coordinate system ICS into a position (coordinates) in the radar coordinate system RCS using Equations (1) and (2). Specifically, the camera 20 converts the coordinates (u1, v1) of the person Ps1 in the image coordinate system ICS into the coordinates (x1, y1, z1) in the radar coordinate system RCS.
The camera 20 transmits, to the monitoring radar 10, the coordinates of person Ps1 and the coordinates of vehicles Vc1 and Vc2 in the image coordinate system ICS after conversion processing from the radar coordinate system RCS to the image coordinate system ICS. The monitoring radar 10 stores data of the three-dimensional radar map RMP1 corresponding to the radar coordinate system RCS in the memory 12 or the like. The radar processor 11 (monitoring radar 10) may superimpose information (frame Fp1 or the like) indicating the person Ps1 on the coordinates of the person Ps1 in the radar coordinate system RCS (see
The external parameters and the internal parameters of the camera 20 may be stored in the monitoring radar 10, and the coordinates (u1, v1) in the image coordinate system ICS may be converted into the coordinates (x1, y1, z1) in the radar coordinate system RCS by using Equations (1) and (2) in the monitoring radar 10.
In addition, the database 33 may store information indicating coordinates indicating a predetermined range, position, or the like in the radar coordinate system RCS and/or coordinates indicating a predetermined range, position, or the like in the camera coordinate system CCS.
In the present embodiment, it is possible to accurately convert coordinates in the image coordinate system ICS into coordinates in the camera coordinate system CCS on the basis of the distance from the origin of the camera coordinate system CCS to the positions (coordinates) of two arbitrary points on the projected surface (in other words, the camera image CAP1) separated by a focal distance f, the focal distance f, and the actual distance (actual measurement value or the like) between two arbitrary points on the camera image CAP1. The two arbitrary points on the camera image CAP1 are, for example, a point corresponding to the top of the head of a person and a point corresponding to the feet of the person in terms of the height (average value) of the person. In addition, with a vehicle, the two arbitrary points on the camera image CAP1 are a point corresponding to the top of the vehicle and a point corresponding to the bottom of the wheel. With a vehicle, it is also possible to estimate the vehicle type according to the vehicle height.
Next, an operation procedure for associating the coordinates of the detected object in the radar coordinate system with the coordinates of the imaged object in the camera coordinate system in the monitoring system 100 will be described.
In
Information (an example of second installation information) including information of a camera installation position on a map (for example, a site map of a monitoring area) of the fixed camera 20A and information of a camera imaging direction is input to the server processor 31 by a user using the operation device 60 (step St2). Although the information of the camera field of view is stored in camera 20, the server 30 may pre-store the information of the camera field of view of the fixed camera 20A. The fixed camera 20A may be provided with a GPS receiver, and the position information of the fixed camera 20A measured by the GPS may be sent from the fixed camera 20A to the server 30 as information of the camera installation position to be shared.
The server processor 31 generates and sets a calculation formula using the information obtained in steps St1 and St2 (step St3). In step St3, the server processor 31 generates and sets calculation formulas (Equations (1) and (2): see
Next, with reference to
First, the series of processing steps executed by the monitoring radar 10 will be described. The monitoring radar 10 emits electromagnetic waves in the first monitoring area AR1 (step StR11). The monitoring radar 10 receives the reflected wave of the electromagnetic wave reflected in step StR11 (step StR12). The reflected wave received by the monitoring radar 10 in step StR12 corresponds to a reflected wave when an electromagnetic wave emitted by the monitoring radar 10 in step StR11 is reflected by an object present in the first monitoring area AR1.
The monitoring radar 10 inputs the reflected wave received in step StR12 to the radar IC 13n. The radar IC 13n detects an object present in the first monitoring area AR1 by executing signal processing using the reflected wave. Among the objects present in the first monitoring area AR1, the object detected by the radar IC 13n corresponds to the detected object. The result of the signal processing by the radar IC 13n is sent to the radar processor 11. The radar processor 11 obtains the coordinates in the radar coordinate system RCS indicating the position of the detected object on the basis of the result of the signal processing by the radar IC 13n. In addition, the radar processor 11 may obtain the movement speed of the detected object, the type of the detected object, and the like as the detected object attribute information on the basis of the result of the signal processing result by the radar IC 13n. The radar processor 11 may obtain the movement speed of the detected object obtained by the radar IC 13n. Then, the radar processor 11 assigns a radar ID for identifying the detected object to the object detected by the radar IC 13n among the objects present in the first monitoring area AR1 (the objects 1, 2, 4, and 5 in a table TBL0, see
In step StR13, the radar ID “1001” is assigned to the object 1. The radar ID “1002” is assigned to the object 2. The radar ID “1003” is assigned to the object 4. The radar ID “1001” is assigned to the object 5 (see
The radar processor 11 converts the coordinates in the radar coordinate system RCS indicating the position of the detected object assigned with the radar ID into coordinates in an arbitrary coordinate system by using the calculation formula generated in step St3 (see
Next, a series of processing steps executed by the fixed camera 20A will be described. The fixed camera 20A images the second monitoring area AR2 (step StC11). The image (camera image CAP1) of the second monitoring area AR2 captured by the fixed camera 20A in step StC11 is input to the camera processor 21A from the imaging unit 23A. Next, the camera processor 21A causes the AI processing unit 25A to execute image analysis of the camera image CAP1. Then, the camera processor 21A obtains the position (coordinates in the image coordinate system ICS) of the object included in the camera image CAP1 on the basis of the analysis result of the camera image CAP1 by the AI processing unit 25A (step StC12). The AI calculation processing unit 251A executes, for example, processing to determine the presence or absence of an object included in the camera image CAP1. Among the objects present in the second monitoring area AR2, an object recognized as an object included in the camera image CAP1 via image analysis performed by the AI processing unit 25A corresponds to the imaged object. That is, in step StC12, the camera processor 21A obtains the position of the imaged object. Then, the camera processor 21A assigns a camera ID for identifying an imaged object to the object included in the camera image CAP1 among objects present in the second monitoring area AR2 (step StC12). The camera ID is an example of a second identifier according to the present embodiment.
Next, the camera processor 21A causes the AI processing unit 25A to perform attribute classification to extract imaged object attribute information. The camera processor 21A associates together the imaged object attribute information obtained as a result of the attribute classification processing executed by the AI processing unit 25A and the position of the imaged object and the camera ID (see objects 1, 3, and 5 in the table TBL0 in
In the present embodiment, the attributes of the imaged object indicate a characteristic element of the imaged object. For example, the attribute of the imaged object is at least one of type, gender, age bracket, height, color of clothes, vehicle type, vehicle color, or number plate of the imaged object, a score indicating accuracy (attribute similarity) when the imaged object attribute information is classified, and movement speed of the object. The type of imaged object indicates whether the imaged object is a person, a vehicle, a two-wheeled vehicle, an animal, or the like. The vehicle type indicates the type of vehicle including, for example, sedan, wagon, minivan, and the like. The AI calculation processing unit 251A executes processing to determine whether the imaged object is a person, a vehicle, or a two-wheeled vehicle using the position information of the imaged object and the imaged object attribute information.
In step StC13, the camera ID “2001” is assigned to the object 1. The camera ID “2002” is assigned to the object 3. The camera ID “2003” is assigned to the object 5 (see
The camera processor 21A converts the coordinates in the image coordinate system ICS indicating the position of the imaged object assigned with the camera ID into coordinates in an arbitrary coordinate system by using the calculation formula of step St3 (see
Next, the series of processing steps executed by the monitoring radar 10 will be described with reference to
As illustrated in the table TBL0, at the time of step StS11, the objects to which a radar ID is assigned are the objects 1, 2, 4, and 5, and the objects to which a camera ID is assigned are the objects 1, 3, and 5. In the example illustrated in
There is a high likelihood that the converted detected object coordinates (or the coordinates in the radar coordinate system RCS) and the converted imaged object coordinates relating to an identical object are the same. That is, the server processor 31 compares the converted detected object coordinates (or the coordinates in the radar coordinate system RCS) corresponding to the radar ID “1001” with the converted imaged object coordinates corresponding to the camera IDs “2001”, “2002”, and “2003”. As illustrated in
When the server processor 31 determines that the detected object and the imaged object are an identical object (YES in step StS11), the server processor 31 assigns a server ID (an example of a third identifier) for identifying the detected object determined to be the identical object in association with the radar ID of the detected object determined to be the identical object and the camera ID of the imaged object determined to be the identical object (objects 1 and 5 in a table TBL1, see
In step StS12, the server processor 31 assigns the server ID “3001” to the radar ID “1001” and the camera ID “2001” and assigns the server ID “3004” to the radar ID “1004” and the camera ID “2003” (see
Relating to the detected object corresponding to the radar ID sent from the server 30 in step StS12, the radar processor 11 associates together the detected object attribute information obtained by the monitoring radar 10 and the imaged object attribute information associated with the radar ID (step StR16). The imaged object attribute information of the imaged object associated with the radar ID corresponds to the imaged object attribute information obtained by the fixed camera 20A relating to the imaged object determined to be the identical object as the detected object corresponding to the radar ID in step StS11.
That is, in step StR16, the radar processor 11 associates the imaged object attribute information relating to the camera ID “2001” corresponding to the server ID “3001” to the radar ID “1001”. Also, in step StR16, the radar processor 11 associates the imaged object attribute information relating to the camera ID “2003” corresponding to the server ID “3004” to the radar ID “1004”.
In this manner, the monitoring radar 10 can obtain the detected object attribute information obtained by the monitoring radar 10 relating to the detected object assigned with the server ID and the imaged object attribute information obtained by the fixed camera 20A. In the monitoring system 100, after step StR16, the processing illustrated in
In the monitoring system 100, as a result of the processing in
That is, in the series of processing steps in
On the other hand, in step StS11, when it is determined that the detected object and the imaged object are not an identical object (NO in step StS11), the server processor 31 executes the processing of step StS13. In step StS13, the server processor 31 determines whether or not an object not detected by the monitoring radar 10 has been imaged by the fixed camera 20A on the basis of the converted detected object coordinates and the converted imaged object image (step StS13).
As illustrated in the table TBL0, at the time of step StS11, the objects to which a radar ID is assigned are the objects 1, 2, 4, and 5, and the objects to which a camera ID is assigned are the objects 1, 3, and 5. Since the objects 1 and 5 are determined to be YES in Step StS11, the server processor 31 executes the processing of Step StS13 on the basis of the converted imaged object coordinates of the object 3 in the example illustrated in
That is, the server processor 31 determines whether or not there are converted detected object coordinates (or coordinates in the radar coordinate system RCS) that are the same as the converted imaged object coordinates corresponding to the camera ID “2002”. As illustrated in
When the server processor 31 determines that the fixed camera 20A has imaged an object that has not been detected by monitoring radar 10 (YES in step StS13), the server processor 31 assigns a server ID and a radar ID for the monitoring radar 10 to the imaged object imaged by the fixed camera 20A (the object 3 in table TBL0, see
In step StS14, the server processor 31 assigns the server ID “3005” and the radar ID “3005” to the camera ID “2002” (see
The radar processor 11 newly generates information of a detected object (specifically, an object imaged by the fixed camera 20A and not detected by the monitoring radar 10) using the information sent from the server 30 in step StS14 (step StR17). In the following description, an object imaged by the camera 20 and not detected by the monitoring radar 10 may be referred to as a “detection target object”. For example, the radar processor 11 assigns a radar ID to a detection target object and associates attribute information of the detection target object and a radar ID together. The attribute information of the detection target object corresponds to the imaged object attribute information obtained by the fixed camera 20A relating to the imaged object corresponding to the detection target object. In this manner, the monitoring radar 10 can associate together the imaged object attribute information of the object that has not been detected by monitoring radar 10 but has been imaged by fixed camera 20A and the radar ID that enables the monitoring radar 10 to perform tracing processing. In the monitoring system 100, after step StR17, the processing illustrated in
When it is determined in step StS13 that the object detected by the monitoring radar 10 has not been imaged by fixed camera 20A (NO in step StS13), the server processor 31 assigns a server ID to the detected object detected by the monitoring radar 10 (objects 2 and 4 in table TBL0, see
As illustrated in the table TBL0, at the time of step StS11, the objects to which a radar ID is assigned are the objects 1, 2, 4, and 5, and the objects to which a camera ID is assigned are the objects 1, 3, and 5. Note that the objects 1 and 5 are determined to be YES in step StS11, and the object 3 is determined as YES in step StS13. Thus, in the example illustrated in
That is, the server processor 31 executes the processing of step StS15 using the converted detected object coordinates (or the coordinates in the radar coordinate system RCS) corresponding to the radar ID “1002” and the converted detected object coordinates (or the coordinates in the radar coordinate system RCS) corresponding to the radar ID “1004”. As illustrated in
As a result of the processing in
Note that the object 6 has not been detected by the monitoring radar 10 and has not been detected by the camera 20. Thus, since the server 30 cannot learn of the presence of the object 6, the server 30 cannot assign a server ID (see
Next, an operation procedure for associating the coordinates in the radar coordinate system indicating the position of the detected object with the coordinates in the camera coordinate system indicating the position of the imaged object in the monitoring system 100 will be described with reference to
The PTZ camera 20B performs pan rotation and/or tilt rotation of the camera lens and performs adjustment such as zoom processing for increasing or decreasing an imaging magnification. Thus, in the description in
In the process of step StR14 in
The camera processor 21B calculates the positions of the rotary motor 261 and the zoom motor 262 (step StC21). In step StC21, the camera processor 21B uses the calculation formula generated in step St3 (see
The camera processor 21B causes the AI processing unit 25B to execute image analysis using the camera image CAP1 of step StC22 as the input. Then, the camera processor 21B obtains the position (coordinates in the image coordinate system ICS) of the imaged object in the camera image CAP1 on the basis of the analysis result of the camera image CAP1 by the AI processing unit 25B (step StC23). An object recognized as an object included in the camera image CAP1 via image analysis performed by the AI processing unit 25B corresponds to the imaged object. The camera processor 21B assigns a camera ID for identifying an imaged object to the object included in the camera image CAP1 (step StC23). The PTZ camera 20B images the imaged object assigned with a camera ID to track the movement path or a lingering state of the object detected by the monitoring radar 10.
Next, the camera processor 21B causes the AI processing unit 25B to perform attribute classification to extract imaged object attribute information. The camera processor 21B associates together the imaged object attribute information obtained as a result of the attribute classification processing executed by the AI processing unit 25B and the position of the imaged object and the camera ID (step StC24).
The camera processor 21B converts the coordinates in the image coordinate system ICS indicating the position of the imaged object assigned with the camera ID into coordinates in the radar coordinate system RCS by using the calculation formula generated in step St3 (see
On the basis of the signal processing in step StR13, the radar processor 11 determines whether or not the monitoring radar 10 has detected the imaged object corresponding to the camera ID sent from the PTZ camera 20B in step StC26 (step StR21).
When the radar processor 11 determines that the monitoring radar 10 has detected the imaged object captured by the PTZ camera 20B (YES in step StR21), the radar processor 11 executes the processing of step StR22. That is, the radar processor 11 associates together the attribute information obtained by the monitoring radar 10 and the imaged object attribute information corresponding to the camera ID sent from PTZ camera 20B for the detected object assigned with a radar ID (step StR22). The detected object assigned with a radar ID corresponds to an object detected by the monitoring radar 10 among objects present in the first monitoring area AR1. In this manner, the monitoring radar 10 can obtain the detected object attribute information and the imaged object attribute information with respect to an identical object detected by the monitoring radar 10 and imaged by the PTZ camera 20B. After step StR22, the monitoring system 100 repeats the processing in
On the other hand, in step StR21, when the radar processor 11 determines that the monitoring radar 10 has not detected the imaged object captured by the PTZ camera 20B (NO in step StR21), the radar processor 11 executes the processing of step StR23. That is, the radar processor 11 generates information of a detection target object (specifically, an object imaged by the PTZ camera 20B and not detected by the monitoring radar 10) using the information sent from the PTZ camera 20B in step StC26 (step StR23). For example, the radar processor 11 assigns a new radar ID to the detection target object, and associates together the attribute information of the detection target object (that is, the imaged object attribute information obtained by PTZ camera 20B with respect to the imaged object corresponding to the detection target object) and the radar ID. As described above, the monitoring radar 10 associates together the imaged object attribute information of the object that has not been detected by the monitoring radar 10 but has been imaged by the PTZ camera 20B and the radar ID, and thus the monitoring radar 10 can execute the tracking processing. After step StR23, the monitoring system 100 repeats the processing in
Next, a processing example using the result of associating the coordinates of the detected object in the radar coordinate system with the post-coordinate-converted coordinates of the imaged object in the radar coordinate system in the monitoring system 100 will be described.
Note that in
With reference to
As illustrated in
When the server processor 31 determines that the detected object and the imaged object are an identical object (YES in step StS11), the server processor 31 determines whether or not an imaged object assigned with the same camera ID is present in the camera images of the plurality of cameras 20 (step StS22). When an imaged object assigned with the same camera ID is not present in the camera images of the plurality of cameras 20 (NO in step StS22), the processing proceeds to step StS25.
On the other hand, when the server processor 31 determines that an imaged object assigned with the same camera ID is present in the camera images of the plurality of cameras 20 (YES in step StS22), the server processor 31 selects, from among the plurality of captured camera images, the camera image CAP1 having a high score in terms of attribute classification (step StS23). After step StS23, the server processor 31 proceeds to step StS25. A camera image having a high attribute classification score corresponds to, for example, an image in which an imaged object such as a person in the camera image is facing the front (that is, toward the camera 20) or an image in which a face portion of the person is clear to such an extent that the area of the face portion is greater than a predetermined number of pixels. In step StS23, the server processor 31 may select one camera image having the highest attribute classification score as the camera image CAP1. It is needless to say that this specific example of the camera image having a high attribute classification score is not limited to the image described above. In this manner, when an identical object is imaged by the plurality of cameras 20, the state of the imaged object can be more accurately grasped.
When the server processor 31 determines that the detected object and the imaged object are not an identical object (NO in step StS11), the server processor 31 executes the processing of step StS13. That is, the server processor 31 determines whether or not an object not detected by the monitoring radar 10 has been imaged by the cameras 20 on the basis of the converted detected object coordinates and the converted imaged object coordinates (step StS13). When it is determined that the object which has not been detected by the monitoring radar 10 has not been imaged by the cameras 20 (NO in step StS13), the server processor 31 ends the processing in
On the other hand, when the server processor 31 determines that the cameras 20 has imaged the object that has not been detected by the monitoring radar 10 (YES in step StS13), the server processor 31 executes the processing of step StS24. That is, the server processor 31 superimposes and displays a marker (for example, a circular image or the like) indicating the imaged object (for example, the person Ps1) at the position of the imaged object on the two-dimensional map input in step St11 in
The server processor 31 generates the superimposed image IMP1 indicating the camera image CAP1 of the imaged object (for example, the person Ps1) and the attribute information relating to the detected object and/or the imaged object (step StS25). The server 30 generates a superimposed screen WD1 (see
Next, with reference to
As illustrated in
The user of the monitoring system 100 can designate the no-entry area AR10 by operating the operation device 60. For example, a shape other than a rectangle may be designated as the no-entry area AR10. For example, as an example of the no-entry area AR10, a no-entry line BNL1 for detecting the presence or absence of an object at a position a predetermined distance away from a reference position (in
As illustrated in
No. 1 of the alarm activation rule TBL2 indicates an example in which an alarm is activated when an object crosses the no-entry line BNL1 (line cross), the object is a person, and the attribute of the object is red. The attribute of the object being red corresponds to, for example, a case where the object is a person and the person is wearing red clothing, but it is not limited to these examples. The alarm activation rule TBL2 for a no-entry area can be edited by the user using the operation device 60, and the edited alarm activation rule may be stored in the memory 32.
As illustrated in
The radar processor 11 executes tracking processing to track the object using the result of the detection processing executed by the detection unit 13 (step StR31). The radar processor 11 determines whether or not the attribute information (the detected object attribute information and/or the imaged object attribute information) relating to the object to be tracked corresponds to the alarm activation rule TBL2 (step StR32). When it is determined that the attribute information relating to the object to be tracked (that is, the detected object attribute information and/or the imaged object attribute information relating to the object) does not correspond to the alarm activation rule TBL2 (NO in Step StR32), the processing of the monitoring system 100 illustrated in
On the other hand, when the radar processor 11 determines that the attribute information (the detected object attribute information and/or the imaged object attribute information) relating to the object to be tracked corresponds to the alarm activation rule TBL2 (YES in step StR32), the radar processor 11 executes the processing of step StR33. That is, the radar processor 11 generates notification information for activating an alarm and sends the notification information to the server 30 (step StR33). The server processor 31 notifies a predetermined notification destination, such as a user terminal, of the alarm activation. Here, the notification information for alarm activation includes, for example, at least the attribute information of an object to be tracked (the detected object attribute information and/or the imaged object attribute information), a position of the object to be tracked (for example, a position in the radar coordinate system RCS), and information such as the current time. In addition, the server processor 31 may generate control information for moving the security robot 40 and information for issuing a threat, a warning, or a similar action targeting the object, and may notify the security robot 40 of this information as an alarm.
As described above, the monitoring system 100 of the present disclosure notifies a user terminal or the like of notification information including not only the presence or absence of an object but also various pieces of information relating to the object obtained by the monitoring radar 10 and/or the camera 20. Thus, the monitoring system 100 can improve the detection accuracy of an object present in the monitoring area.
In addition, since the monitoring system 100 can collect various kinds of information relating to the object detected by the monitoring radar 10, it is possible to improve the detection accuracy of the object present in the monitoring area (for example, the first monitoring area AR1 and the second monitoring area AR2).
In addition, the monitoring system 100 can store an alarm activation rule for an alarm indicating the presence of an object that has entered a no-entry area and can accurately perform notification of the entry by the object by executing entry detection processing according to the alarm activation rule.
In addition, the monitoring system 100 can accurately detect only objects that perform a designated abnormal behavior in an arbitrary designated area.
In addition, the monitoring system 100 can accurately detect only objects corresponding to a designated condition as attribute information of the object.
In addition, by displaying the position of the object on the map MP1 in a superimposed manner, the monitoring system 100 makes it easier for a user viewing the map MP1 to grasp the position of the object.
In addition, since the monitoring system 100 can display not only the position of the object on the map MP1 but can also display the camera image of when the object was imaged and the attribute information of the object together on the map MP1, it is possible for the user to grasp detailed information of the object.
In addition, the monitoring system 100 makes it easy for the user to visually comprehend what kind of characteristic element a person has at what position.
In addition, by comprehensively using the monitoring radar 10 and the plurality of cameras 20, the monitoring system 100 can not only further improve the detection accuracy of the object but also extract more detailed information such as attribute information of the object. In addition, the monitoring system 100 displays a camera image more suitable for extraction of attribute information of the object and the attribute information obtained from the camera image, and thus can accurately present highly reliable information regarding the object to the user.
In addition, the monitoring system 100 can output highly reliable information regarding the object by using any one of a score indicating the accuracy of the attribute information included in the attribute information, the size of the object, or both the score and the size of the object.
Although various embodiments have been described above with reference to the drawings, it goes without saying that the present disclosure is not limited to such examples. A person skilled in the art can conceive of various changes, modifications, substitutions, additions, deletions, and equivalents within the scope described in the claims, and it should be understood that these also naturally fall within the technical scope of the present disclosure. The components in the various embodiments described above may be combined as desired to an extent that does not depart from the scope of the invention.
This application is based on Japanese Patent Application No. 2022-052014 filed on Mar. 28, 2022, the contents of which are incorporated herein by reference.
The present disclosure is useful as a monitoring system and a monitoring method for improving the detection accuracy of an object present in a monitoring area.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022-052014 | Mar 2022 | JP | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2023/006794 | 2/24/2023 | WO |