Vision-Based Seat Belt Detection System

Abstract

The invention is a system and method that detects seat belt-related features using an image sensor. Reflective materials are optionally applied onto or embedded into the seat belt webbing, buckle, nest and handle to reflect patterns from infrared illumination to the image sensor. Software compounds these findings to result an overall ‘Belted’ and ‘Unbelted’ detection output. A temporal model software assists in stabilizing the decision in unsure situations by adding past images' decisions into the current decision. ‘Twisted belt’ and ‘Seat belt buckled behind back/seat’ situations can be also detected to notify the driver about unsafe occupant situations in the vehicle. The detection is applicable to safety belt detection for the driver seat, front passenger seat, back or any additional seats in vehicles.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the present invention will now be described, by way of example only, with reference to the attached Figures, wherein:

FIG. 1 is a schematic view of a seat belt detection system in accordance with a first aspect of the invention;

FIGS. 2 a to 2c are all front plan view of a portion of a different seat belt that can be used in the seat belt detection system shown in FIG. 1;

FIG. 3 a is a decision table using two detectors and tri-state logic for determining the state of the seat belt detection system shown in FIG. 1;

FIG. 3 b is a decision table using two detectors and binary logic for determining the state of the seat belt detection system shown in FIG. 1;

FIG. 4 is a decision table using three detectors and tri-state logic for determining the state of the seat belt detection system shown in FIG. 1;

FIG. 5 is a decision table using three detectors and tri-state logic for determining the state of failure for the seat belt detection system shown in FIG. 1;

FIG. 6 is a flow chart for determining the state for the seat belt detection system shown in FIG. 1, in accordance with another embodiment of the invention; and

FIG. 7 is a table showing different possible scat belt states in accordance with the flow chart shown in FIG. 6.

Claims

1. A seat belt detection system for a vehicle, comprising: a seat belt assembly, having a plurality of indicators distributed over predetermined portions of the seat belt assembly;an image sensor, located within the vehicle as to be able to receive an image of at least a portion of the seat belt assembly;an image processor, operable to analyze the image to identify said plurality of indicators for image analysis; the image analysis matching the identified plurality of indicators to a predefined set of indicators that characterize at least one particular status for the seat belt assembly.

2. The seat belt detection system of claim 1, wherein the seat belt assembly includes: a seat belt nest, having a webbing extending from the seat belt nest;a seat belt handle movably mounted to the webbing, the seat belt handle having a latching plate; anda buckle, mounted to a vehicle seat and operable to receive the latching plate from the seat belt handle.

3. The seat belt detection system of claim 2, further comprising: an infrared light source that illuminates the seat belt assembly; and wherein the plurality of indicators distributed over the seat belt assembly are operable to reflect the infrared light source to the image sensor, and the image sensor is operable to receive the reflected infrared light from the plurality of indicators.

4. The seat belt detection system of claim 3, wherein the image processor is operable to characterize a seat belt status as “Belted” or “Unbelted” based upon the interpretation of at least one of the plurality of indicators.

5. The seat belt detector system of claim 4, wherein the plurality of indicators includes at least one of a nest indicator, an outer web indicator, an inner web indicator, a seat belt handle indicator, and a buckle indicator.

6. The seat belt detector system of claim 5, wherein the particular status indicator includes at least one of a “Seat belt nest is seen” indicator, a “Seat belt handle is nested” indicator, a “Seat belt buckle is seen” indicator, a “Seat belt handle is buckled” indicator, a “Seat belt web is seen” indicator, a “Seat belt web is webbed” indicator, a “Seat belt web is twisted” indicator, and a “Seat belt web is behind occupant's back” indicator.

7. The seat belt detector system of claim 6, wherein the particular status is defined as one of a pair of opposing binary conditions.

8. The seat belt detection system of claim 7, wherein the particular status is further defined as one of a pair of opposing binary conditions or an “Unsure” condition if the image processor is unable to recognize a particular indicator.

9. The seat belt detector system of claim 7, wherein the seat belt assembly is characterized as “Belted” or “Unbelted” based upon comparing at least two particular status indicators to a predefined set of indicators that characterize the seat belt assembly as “Belted” or “Unbelted”.

10. The seat belt detector system of claim 8, wherein the image processor is operable to store a previously-recorded image of the seat belt assembly, and use the previously-recorded image of the seat belt assembly to characterize a particular status that is currently defined as “Unsure”.

11. The seat belt detection system of claim 9, wherein the image sensor is operable to receive an image of at least a portion of multiple seat belt assemblies from at least two vehicle seats.

12. The seat belt detection system of claim 11, wherein the at least two vehicle seats includes a rear passenger seat.

13. The seat belt detection system of claim 12, wherein the image sensor installed in a roof console within the vehicle.

14. The seat belt detection system of claim 12, wherein the image sensor installed in a vehicle pillar.

15. A method for determining whether a seat belt assembly is buckled, the seat belt assembly having a plurality of indicators distributed over predetermined portions of the seat belt assembly using image recognition, the method comprising: illuminating at least a portion of the seat belt assembly using a light source;receiving a reflected image from at least a portion of the seat belt assembly at an image sensor;identifying at least one of the plurality of indicators from the reflected image using an image processor; andcomparing the identified at least one of the plurality of indicators to a predefined set of indicators that characterizes at least one particular status of the seat belt assembly.

16. The method of claim 15, wherein the plurality of indicators includes an indicator on a seat belt handle and an indicator on a seat belt nest, and where characterizing the at least one particular status of the seat belt assembly includes a nested status one of “Nested” and “Not Nested”.

17. The method of claim 16, wherein the plurality of indicators further includes an indicator on a seat belt buckle, and where characterizing the at least one particular status of the seat belt assembly includes a buckled status one of “Buckled” and “Not Buckled”.

18. The method of claim 17, wherein the plurality of indicators further includes an indicator on a seat belt webbing, and where characterizing the at least one particular status of the seat belt assembly includes a web status one of “Webbed” and “Not Webbed”.

19. The method of claim 17, wherein identifying the indicator on the seat belt handle proximate to the indicator on the seat belt buckle characterizes the buckled status of the seat belt assembly as “Buckled”, and where identifying the indicator on the seat belt handle displaced away from the indicator on the seat belt buckle by a predetermined distance characterizes the buckled status of the seat belt assembly as “Not Buckled”.

20. The method of claim 19, wherein a belted status of the seat belt assembly is characterized as “Belted” if it is currently characterized as “Buckled” and “Webbed”, and is otherwise characterized as “Unbelted”.

21. The method of claim 17, wherein characterizing the particular status of the seat belt assembly includes a twisted web status one of “Twisted web” and “Not twisted web”.

22. The method of claim 19, wherein when the seat belt assembly is characterized as “Buckled” and also “Not webbed”, the seat belt assembly is further characterized as being “improperly belted”.

23. The method of claim 22, wherein the seat belt assembly is characterized as “Belted” or “Unbelted” based upon comparing the nested status, the buckled status and the webbed status to a predefined set of indicators.

24. The method of claim 15, wherein at least one particular status of the seat belt assembly can be characterized as “Unsure” when at least one of the plurality of indicators is not reflected back into the image sensor.

25. The method of claim 24, further comprising: recalling a previously-recorded image of the seat belt assembly from memory and using the previously-recorded image of the seat belt assembly to characterize a particular status that is currently defined as “Unsure”.

26. The method of claim 15, wherein the plurality of indicators use an infrared reflective material, and where the light source illuminating the at least a portion of the seat belt assembly uses an infrared light source.

27. The method of claim 26, wherein identifying the at least one of the plurality of indicators by the image processor includes using edge filters on the reflected image, and where the predefined set of indicators used for comparison includes a predefined set of edge features to be compared against.

28. The method of claim 26, wherein identifying the at least one of the plurality of indicators by the image processor includes decomposing wavelet coefficients from the reflected image using known wavelet filters, and where the predefined set of indicators used for comparison includes predefined wavelet-based feature vectors generated from videos of the seat belt assembly.