Time-of-flight (TOF) cameras collect distance data from a scene. However, it can be difficult to collect accurate distance data from moving objects.
A light-sensitive pixel includes an evacuated cavity formed in an insulating substrate. The light-sensitive pixel further includes a photoelectric cathode for generating electrons responsive to light incident on the light-sensitive pixel. The photoelectric cathode is located in the evacuated cavity. The light-sensitive pixel also includes a plurality of anodes for collecting electrons generated at the photoelectric cathode.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Furthermore, the claimed subject matter is not limited to implementations that solve any or all disadvantages noted in any part of this disclosure.
Time-of-flight (TOF) cameras capture distance data. Thus, a three-dimensional image of an object captured by a TOF camera may be generated based on the distance data collected. In a typical TOF camera, light pulses of any suitable wavelength (e.g., one or more wavelengths in an infrared, near infrared, visible, and/or ultraviolet region) are transmitted from the TOF camera to an object. The image light pulses illuminate and are reflected by the object. The return image light is received at a photosensitive surface of the TOF camera. By measuring the time at which the return image light is received at the photosensitive surface, the TOF camera may estimate the distance of various features of the object from the camera. Because light is typically returned relatively sooner from a near feature than from a far feature, time-dependent measurement and quantification of the return image light may provide distance information about the object's features.
It can be more difficult to generate intense light pulses for illuminating the distant object than to generate a train of light pulses comparatively less intense. Thus, some TOF cameras perform the time-dependent measurement by a “range gating” technique. In typical range gating approaches, collection of light at the photosurface is divided (or “gated”) into plural discrete gating events of known duration. By integrating the light received from multiple pulses at the photosurface, the TOF camera may better distinguish return image light from ambient light, potentially improving the accuracy of the distance data.
Further, some TOF cameras may intermittently transmit pulses of normalization light that are reflected from the object and collected at the TOF camera. The collected return normalization light measurement may be used to calibrate the target object's reflectivity light from the light collected during the gated time periods.
However, a number of factors can adversely affect the accuracy of the distance measurements described above. For example, image light and normalization light are often imaged in different frames and acquired at different times. The acquisition times for the two events may be separated by a delay time at least equal to a time for reading and resetting each frame. For an object in motion, the delay time may cause a mismatch where the same pixel receives return image light and return normalization light from different features of an object or scene rather than from the same feature. Mismatches may also result from situations where the same pixel registers return image light and return normalization light from the same feature at different distances from the camera.
Consequently, the distance estimation derived from a mismatch may be faulty. Further, for some TOF camera systems, the gated time periods may have very short durations that may result in an inaccurate distance estimation. Light pulse widths, the short durations of exposure periods, and typical quantum efficiencies on the order of about 10% that characterize conventional photosurfaces used to acquire measurements of gated light, may result in relatively large errors in the measurements due to shot noise. Other distance estimation errors may result from reduction in the modulation ratio between the on and off states of the photosurface.
Accordingly, various embodiments of light-sensitive pixels for TOF cameras and methods for operating such pixels are provided herein that reduce or substantially eliminate delay times between successive gating time periods and/or normalization time periods, such that the accuracy of the distance estimation may be comparatively increased.
As shown in
Return image light 132 is reflected from object 102 and is collected at photosurface 120 of light collector 108. Photosurface 120 comprises one or more light-sensitive pixels (not shown) for collecting return image light 132. In some embodiments, light collector 108 may be controlled by a light collection module 118. In such embodiments, light collection module 118 may control one or more of light gating events and light normalization events for light-sensitive pixels included in photosurface 120.
In the example shown in
As described above, photosurface 120 includes one or more light-sensitive pixels for collecting return image light and return normalization light.
In some embodiments, substrate 202 may be fabricated from an insulating material. Example materials for substrate 202 include, but are not limited to, undoped silicate glass (USG) and doped or undoped silicon, though it will be appreciated that any suitable substrate material may be employed without departing from the scope of the present disclosure.
The example shown in
Optical component 204 includes a photoelectric cathode 210 for generating photoelectrons 216 responsive to light incident on light-sensitive pixel 200. Optical component 204 may be optically transparent in some embodiments, so that light in a visible range of wavelengths may pass through optical component 204. Additionally or alternatively, in some embodiments, optical component 204 may be configured to allow light in an infrared and/or ultraviolet range of wavelengths to pass.
In some embodiments, photoelectric cathode 210 may include a layer of photoelectric material configured to generate photoelectrons 216 in response to incident return image light 132. Example photoelectric materials include, but are not limited to, GaAs, CsO, and AlGaAs. However, it will be appreciated that any suitable photoelectric material may be employed without departing from the scope of the present disclosure. In such embodiments, cavity 206 may be evacuated so that photoelectrons 216 have a sufficiently long mean free path to reach a portion of cavity 206 wherein a plurality of anodes 212 are disposed. In the example shown in
As described above, cavity 206 includes a plurality of anodes 212 for collecting photoelectrons 216 generated at photoelectric cathode 210. In the example shown in
Electrodes 214 are spaced from photocathode 210 according to one or more predetermined design parameters for light-sensitive pixel 200. It is believed that increasing the spacing between electrodes 214 and photocathode 210 may reduce capacitive coupling between electrodes 214 and photocathode 210, potentially increasing a speed at which light-sensitive pixel 200 may switch between each anode 212. Further, as described above, increasing the spacing between electrodes 214 and photocathode 210 may also reduce a probability that photoelectrons 216 may reach electrodes 214, potentially decreasing the charge yield at electrodes 214. However, it will be appreciated that the charge yield may also potentially be reduced as the spacing between electrodes 214 and photocathode 210 is reduced, as a smaller portion of photoelectrons 216 emitted from photocathode 210 may have a suitable trajectory to reach each electrode 214. Thus, suitable spacing may be influenced by an electrode bias voltage during collection, photocathode cross-section, and vacuum level within cavity 206. In one non-limiting example, photocathode 210 may be 2 microns from electrodes 214.
In the example shown in
As shown in the example depicted in
In some embodiments, collector circuit 218 may also include a reset node 234 for resetting anode 212. In the example shown in
It will be appreciated that light-sensitive pixel 200 may be fabricated in any suitable manner without departing from the scope of the present disclosure. For example, in some embodiments, light-sensitive pixel 200 may be fabricated on a silicon substrate. In such embodiments, one or more subtractive processes may be employed to pattern and etch cavity 206 on a first side of the silicon substrate. Further, a through-silicon via may be etched connecting the first side of the silicon substrate to a second, opposite side of the silicon substrate, on which a portion of collector circuit 218 may be formed via various deposition and patterning techniques. In some embodiments, a suitable metallization process may be used to fill the through-silicon via and form electrodes 214. It will be appreciated that, in some embodiments, the first and second sides of the silicon substrate may refer to two silicon substrates initially separated and subsequently bonded via a suitable substrate bonding technique. Finally, as explained above, a suitable deposition process may be used to form photocathode 210 on optical component 204, which may then be bonded to the silicon substrate above cavity 206.
As shown in
Turning back to
In some embodiments, a start time for first return image light collection phase 405A may be based on a predetermined near end point of a distance range for the TOF camera. In the example shown in
Turning back to
In some embodiments, an end time for a second return image light collection phase may be based on a predetermined far end point of the distance range. In the example shown in
In some embodiments, the last collection phase may immediately follow the first collection phase. In the example shown in
Continuing with
In some embodiments, the normalization factor may be generated dynamically at each depth frame by the TOF camera.
In the example shown in
Returning to
Continuing with
Method 300 may additionally or alternatively comprise compensating for ambient light to comparatively reduce measurement errors resulting in part from the influence of ambient light. In some embodiments, ambient light compensation may be achieved by collecting ambient light during a time when a light pulse is not emitted. In this way, the relative amount of ambient light present may be determined. Ambient light compensation is not always required. For example, when the integration time is short enough, the ambient light is low enough, and the accuracy requirements are relaxed enough, there might not be a need to compensate for the ambient light. When ambient light compensation is performed, a signal is collected without operating the illumination. This can be done using any suitable approach, including using anode 212C of
In the example shown in
In some embodiments, anode switching time 710A may be based on a predetermined near end point of a distance range for the time-of-flight camera. In the example shown in
As shown in
The example shown in
In some embodiments, anode switching time 710C may be based on a predetermined far end point of a distance range for the time-of-flight camera. In the example shown in
In the example shown in
A separate normalization light pulse and return normalization light collection phase may not be needed. For example, a reflectivity normalization factor may be generated by summing the light collected in return image light collection phases 705A and 705B of
Continuing with
The above is an ideal case with linear behavior. In some cases, the formula may be:
Or other variations of R1 and R2, where F1 and F2 are functions with unique and monotonic values over the practical range. F1 and F2 may be a practical case when pulse shapes are not as symmetrical as shown in
In some embodiments, the above described methods and processes may be tied to a computing system including one or more computers. In particular, the methods and processes described herein may be implemented as a computer application, computer service, computer API, computer library, and/or other computer program product.
Returning to
Logic subsystem 110 may include one or more physical devices configured to execute one or more instructions. For example, the logic subsystem may be configured to execute one or more instructions that are part of one or more applications, services, programs, routines, libraries, objects, components, data structures, or other logical constructs. Such instructions may be implemented to perform a task, implement a data type, transform the state of one or more devices, or otherwise arrive at a desired result.
Logic subsystem 110 may include one or more processors that are configured to execute software instructions. Additionally or alternatively, logic subsystem 110 may include one or more hardware or firmware logic machines configured to execute hardware or firmware instructions. Processors of the logic subsystem may be single-core or multi-core, and the programs executed thereon may be configured for parallel or distributed processing. Logic subsystem 110 may optionally include individual components that are distributed throughout two or more devices, which may be remotely located and/or configured for coordinated processing. One or more aspects of logic subsystem 110 may be virtualized and executed by remotely accessible networked computing devices configured in a cloud computing configuration.
Data-holding subsystem 112 may include one or more physical, non-transitory, devices configured to hold data and/or instructions executable by the logic subsystem to implement the herein described methods and processes. When such methods and processes are implemented, the state of data-holding subsystem 112 may be transformed (e.g., to hold different data).
It is to be appreciated that data-holding subsystem 112 includes one or more physical, non-transitory devices. In contrast, in some embodiments aspects of the instructions described herein may be propagated in a transitory fashion by a pure signal (e.g., an electromagnetic signal, an optical signal, etc.) that is not held by a physical device for at least a finite duration. Furthermore, data and/or other forms of information pertaining to the present disclosure may be propagated by a pure signal.
The terms “module,” “program,” and “engine” may be used to describe an aspect of TOF camera 104 that is implemented to perform one or more particular functions. In some cases, such a module, program, or engine may be instantiated via logic subsystem 110 executing instructions held by data-holding subsystem 112. It is to be understood that different modules, programs, and/or engines may be instantiated from the same application, service, code block, object, library, routine, API, function, etc. Likewise, the same module, program, and/or engine may be instantiated by different applications, services, code blocks, objects, routines, APIs, functions, etc. The terms “module,” “program,” and “engine” are meant to encompass individual or groups of executable files, data files, libraries, drivers, scripts, database records, etc.
It is to be understood that the configurations and/or approaches described herein are exemplary in nature, and that these specific embodiments or examples are not to be considered in a limiting sense, because numerous variations are possible. The specific routines or methods described herein may represent one or more of any number of processing strategies. As such, various acts illustrated may be performed in the sequence illustrated, in other sequences, in parallel, or in some cases omitted. Likewise, the order of the above-described processes may be changed.
The subject matter of the present disclosure includes all novel and nonobvious combinations and subcombinations of the various processes, systems and configurations, and other features, functions, acts, and/or properties disclosed herein, as well as any and all equivalents thereof.
Number | Name | Date | Kind |
---|---|---|---|
4627620 | Yang | Dec 1986 | A |
4630910 | Ross et al. | Dec 1986 | A |
4645458 | Williams | Feb 1987 | A |
4695953 | Blair et al. | Sep 1987 | A |
4702475 | Elstein et al. | Oct 1987 | A |
4711543 | Blair et al. | Dec 1987 | A |
4751642 | Silva et al. | Jun 1988 | A |
4796997 | Svetkoff et al. | Jan 1989 | A |
4809065 | Harris et al. | Feb 1989 | A |
4817950 | Goo | Apr 1989 | A |
4843568 | Krueger et al. | Jun 1989 | A |
4893183 | Nayar | Jan 1990 | A |
4901362 | Terzian | Feb 1990 | A |
4925189 | Braeunig | May 1990 | A |
5101444 | Wilson et al. | Mar 1992 | A |
5148154 | MacKay et al. | Sep 1992 | A |
5184295 | Mann | Feb 1993 | A |
5229754 | Aoki et al. | Jul 1993 | A |
5229756 | Kosugi et al. | Jul 1993 | A |
5239463 | Blair et al. | Aug 1993 | A |
5239464 | Blair et al. | Aug 1993 | A |
5288078 | Capper et al. | Feb 1994 | A |
5295491 | Gevins | Mar 1994 | A |
5320538 | Baum | Jun 1994 | A |
5347306 | Nitta | Sep 1994 | A |
5385519 | Hsu et al. | Jan 1995 | A |
5405152 | Katanics et al. | Apr 1995 | A |
5417210 | Funda et al. | May 1995 | A |
5423554 | Davis | Jun 1995 | A |
5454043 | Freeman | Sep 1995 | A |
5469740 | French et al. | Nov 1995 | A |
5471051 | Niigaki et al. | Nov 1995 | A |
5495576 | Ritchey | Feb 1996 | A |
5516105 | Eisenbrey et al. | May 1996 | A |
5524637 | Erickson et al. | Jun 1996 | A |
5534917 | MacDougall | Jul 1996 | A |
5563988 | Maes et al. | Oct 1996 | A |
5577981 | Jarvik | Nov 1996 | A |
5580249 | Jacobsen et al. | Dec 1996 | A |
5594469 | Freeman et al. | Jan 1997 | A |
5597309 | Riess | Jan 1997 | A |
5602397 | Pitts | Feb 1997 | A |
5616078 | Oh | Apr 1997 | A |
5617312 | Iura et al. | Apr 1997 | A |
5638300 | Johnson | Jun 1997 | A |
5641288 | Zaenglein, Jr. | Jun 1997 | A |
5677560 | Zimmer | Oct 1997 | A |
5682196 | Freeman | Oct 1997 | A |
5682229 | Wangler | Oct 1997 | A |
5690582 | Ulrich et al. | Nov 1997 | A |
5703367 | Hashimoto et al. | Dec 1997 | A |
5704837 | Iwasaki et al. | Jan 1998 | A |
5715834 | Bergamasco et al. | Feb 1998 | A |
5875108 | Hoffberg et al. | Feb 1999 | A |
5877803 | Wee et al. | Mar 1999 | A |
5913727 | Ahdoot | Jun 1999 | A |
5933125 | Fernie | Aug 1999 | A |
5980256 | Carmein | Nov 1999 | A |
5989157 | Walton | Nov 1999 | A |
5995649 | Marugame | Nov 1999 | A |
6005548 | Latypov et al. | Dec 1999 | A |
6009210 | Kang | Dec 1999 | A |
6054991 | Crane et al. | Apr 2000 | A |
6066075 | Poulton | May 2000 | A |
6072494 | Nguyen | Jun 2000 | A |
6073489 | French et al. | Jun 2000 | A |
6077201 | Cheng et al. | Jun 2000 | A |
6098458 | French et al. | Aug 2000 | A |
6100896 | Strohecker et al. | Aug 2000 | A |
6101289 | Kellner | Aug 2000 | A |
6128003 | Smith et al. | Oct 2000 | A |
6130677 | Kunz | Oct 2000 | A |
6141463 | Covell et al. | Oct 2000 | A |
6147678 | Kumar et al. | Nov 2000 | A |
6152856 | Studor et al. | Nov 2000 | A |
6159100 | Smith | Dec 2000 | A |
6173066 | Peurach et al. | Jan 2001 | B1 |
6181343 | Lyons | Jan 2001 | B1 |
6188777 | Darrell et al. | Feb 2001 | B1 |
6215890 | Matsuo et al. | Apr 2001 | B1 |
6215898 | Woodfill et al. | Apr 2001 | B1 |
6226396 | Marugame | May 2001 | B1 |
6229913 | Nayar et al. | May 2001 | B1 |
6256033 | Nguyen | Jul 2001 | B1 |
6256400 | Takata et al. | Jul 2001 | B1 |
6283860 | Lyons et al. | Sep 2001 | B1 |
6289112 | Jain et al. | Sep 2001 | B1 |
6299308 | Voronka et al. | Oct 2001 | B1 |
6308565 | French et al. | Oct 2001 | B1 |
6316934 | Amorai-Moriya et al. | Nov 2001 | B1 |
6363160 | Bradski et al. | Mar 2002 | B1 |
6384819 | Hunter | May 2002 | B1 |
6411744 | Edwards | Jun 2002 | B1 |
6430997 | French et al. | Aug 2002 | B1 |
6476834 | Doval et al. | Nov 2002 | B1 |
6496598 | Harman | Dec 2002 | B1 |
6503195 | Keller et al. | Jan 2003 | B1 |
6507365 | Inoue et al. | Jan 2003 | B1 |
6539931 | Trajkovic et al. | Apr 2003 | B2 |
6570555 | Prevost et al. | May 2003 | B1 |
6633294 | Rosenthal et al. | Oct 2003 | B1 |
6640202 | Dietz et al. | Oct 2003 | B1 |
6661918 | Gordon et al. | Dec 2003 | B1 |
6681031 | Cohen et al. | Jan 2004 | B2 |
6714665 | Hanna et al. | Mar 2004 | B1 |
6731799 | Sun et al. | May 2004 | B1 |
6738066 | Nguyen | May 2004 | B1 |
6765726 | French et al. | Jul 2004 | B2 |
6788809 | Grzeszczuk et al. | Sep 2004 | B1 |
6801637 | Voronka et al. | Oct 2004 | B2 |
6873723 | Aucsmith et al. | Mar 2005 | B1 |
6876496 | French et al. | Apr 2005 | B2 |
6937742 | Roberts et al. | Aug 2005 | B2 |
6950534 | Cohen et al. | Sep 2005 | B2 |
7003134 | Covell et al. | Feb 2006 | B1 |
7036094 | Cohen et al. | Apr 2006 | B1 |
7038855 | French et al. | May 2006 | B2 |
7039676 | Day et al. | May 2006 | B1 |
7042440 | Pryor et al. | May 2006 | B2 |
7050606 | Paul et al. | May 2006 | B2 |
7058204 | Hildreth et al. | Jun 2006 | B2 |
7060957 | Lange et al. | Jun 2006 | B2 |
7113918 | Ahmad et al. | Sep 2006 | B1 |
7121946 | Paul et al. | Oct 2006 | B2 |
7170492 | Bell | Jan 2007 | B2 |
7184048 | Hunter | Feb 2007 | B2 |
7202898 | Braun et al. | Apr 2007 | B1 |
7222078 | Abelow | May 2007 | B2 |
7227526 | Hildreth et al. | Jun 2007 | B2 |
7259747 | Bell | Aug 2007 | B2 |
7308112 | Fujimura et al. | Dec 2007 | B2 |
7317836 | Fujimura et al. | Jan 2008 | B2 |
7348963 | Bell | Mar 2008 | B2 |
7355648 | Braun et al. | Apr 2008 | B1 |
7359121 | French et al. | Apr 2008 | B2 |
7367887 | Watabe et al. | May 2008 | B2 |
7379563 | Shamaie | May 2008 | B2 |
7379566 | Hildreth | May 2008 | B2 |
7389591 | Jaiswal et al. | Jun 2008 | B2 |
7412077 | Li et al. | Aug 2008 | B2 |
7421093 | Hildreth et al. | Sep 2008 | B2 |
7430312 | Gu | Sep 2008 | B2 |
7436496 | Kawahito | Oct 2008 | B2 |
7450736 | Yang et al. | Nov 2008 | B2 |
7452275 | Kuraishi | Nov 2008 | B2 |
7460690 | Cohen et al. | Dec 2008 | B2 |
7489812 | Fox et al. | Feb 2009 | B2 |
7536032 | Bell | May 2009 | B2 |
7555142 | Hildreth et al. | Jun 2009 | B2 |
7560701 | Oggier et al. | Jul 2009 | B2 |
7570805 | Gu | Aug 2009 | B2 |
7574020 | Shamaie | Aug 2009 | B2 |
7576727 | Bell | Aug 2009 | B2 |
7590262 | Fujimura et al. | Sep 2009 | B2 |
7593552 | Higaki et al. | Sep 2009 | B2 |
7598942 | Underkoffler et al. | Oct 2009 | B2 |
7607509 | Schmiz et al. | Oct 2009 | B2 |
7620202 | Fujimura et al. | Nov 2009 | B2 |
7668340 | Cohen et al. | Feb 2010 | B2 |
7680298 | Roberts et al. | Mar 2010 | B2 |
7683954 | Ichikawa et al. | Mar 2010 | B2 |
7684592 | Paul et al. | Mar 2010 | B2 |
7701439 | Hillis et al. | Apr 2010 | B2 |
7702130 | Im et al. | Apr 2010 | B2 |
7704135 | Harrison, Jr. | Apr 2010 | B2 |
7710391 | Bell et al. | May 2010 | B2 |
7729530 | Antonov et al. | Jun 2010 | B2 |
7746345 | Hunter | Jun 2010 | B2 |
7760182 | Ahmad et al. | Jul 2010 | B2 |
7809167 | Bell | Oct 2010 | B2 |
7834846 | Bell | Nov 2010 | B1 |
7852262 | Namineni et al. | Dec 2010 | B2 |
RE42256 | Edwards | Mar 2011 | E |
7898522 | Hildreth et al. | Mar 2011 | B2 |
8035612 | Bell et al. | Oct 2011 | B2 |
8035614 | Bell et al. | Oct 2011 | B2 |
8035624 | Bell et al. | Oct 2011 | B2 |
8072470 | Marks | Dec 2011 | B2 |
20010003013 | Katsumata | Jun 2001 | A1 |
20070091175 | Iddan et al. | Apr 2007 | A1 |
20080026838 | Dunstan et al. | Jan 2008 | A1 |
20090072122 | Tada et al. | Mar 2009 | A1 |
20100039546 | Cohen et al. | Feb 2010 | A1 |
20100134735 | Nakamura et al. | Jun 2010 | A1 |
20100171813 | Pelman et al. | Jul 2010 | A1 |
20110074274 | Tang et al. | Mar 2011 | A1 |
Number | Date | Country |
---|---|---|
101421848 | Apr 2009 | CN |
201254344 | Jun 2010 | CN |
101904165 | Dec 2010 | CN |
0583061 | Feb 1994 | EP |
08044490 | Feb 1996 | JP |
9310708 | Jun 1993 | WO |
9717598 | May 1997 | WO |
9944698 | Sep 1999 | WO |
2008088481 | Jul 2008 | WO |
2009063472 | May 2009 | WO |
Entry |
---|
Kanade et al., “A Stereo Machine for Video-rate Dense Depth Mapping and Its New Applications”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1996, pp. 196-202,The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA. |
Miyagawa et al., “CCD-Based Range Finding Sensor”, Oct. 1997, pp. 1648-1652, vol. 44 No. 10, IEEE Transactions on Electron Devices. |
Rosenhahn et al., “Automatic Human Model Generation”, 2005, pp. 41-48, University of Auckland (CITR), New Zealand. |
Aggarwal et al., “Human Motion Analysis: A Review”, IEEE Nonrigid and Articulated Motion Workshop, 1997, University of Texas at Austin, Austin, TX. |
Shao et al., “An Open System Architecture for a Multimedia and Multimodal User Interface”, Aug. 24, 1998, Japanese Society for Rehabilitation of Persons with Disabilities (JSRPD), Japan. |
Kohler, “Special Topics of Gesture Recognition Applied in Intelligent Home Environments”, In Proceedings of the Gesture Workshop, 1998, pp. 285-296, Germany. |
Kohler, “Vision Based Remote Control in Intelligent Home Environments”, University of Erlangen-Nuremberg/Germany, 1996, pp. 147-154, Germany. |
Kohler, “Technical Details and Ergonomical Aspects of Gesture Recognition applied in Intelligent Home Environments”, 1997, Germany. |
Hasegawa et al., “Human-Scale Haptic Interaction with a Reactive Virtual Human in a Real-Time Physics Simulator”, Jul. 2006, vol. 4, No. 3, Article 6C, ACM Computers in Entertainment, New York, NY. |
Qian et al., “A Gesture-Driven Multimodal Interactive Dance System”, Jun. 2004, pp. 1579-1582, IEEE International Conference on Multimedia and Expo (ICME), Taipei, Taiwan. |
Zhao, “Dressed Human Modeling, Detection, and Parts Localization”, 2001, The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA. |
He, “Generation of Human Body Models”, Apr. 2005, University of Auckland, New Zealand. |
Isard et al., “Condensation—Conditional Density Propagation for Visual Tracking”, 1998, pp. 5-28, International Journal of Computer Vision 29(1), Netherlands. |
Livingston, “Vision-based Tracking with Dynamic Structured Light for Video See-through Augmented Reality”, 1998, University of North Carolina at Chapel Hill, North Carolina, USA. |
Wren et al., “Pfinder: Real-Time Tracking of the Human Body”, MIT Media Laboratory Perceptual Computing Section Technical Report No. 353, Jul. 1997, vol. 19, No. 7, pp. 780-785, IEEE Transactions on Pattern Analysis and Machine Intelligence, Caimbridge, MA. |
Breen et al., “Interactive Occlusion and Collusion of Real and Virtual Objects in Augmented Reality”, Technical Report ECRC-95-02, 1995, European Computer-Industry Research Center GmbH, Munich, Germany. |
Freeman et al., “Television Control by Hand Gestures”, Dec. 1994, Mitsubishi Electric Research Laboratories, TR94-24, Caimbridge, MA. |
Hongo et al., “Focus of Attention for Face and Hand Gesture Recognition Using Multiple Cameras”, Mar. 2000, pp. 156-161, 4th IEEE International Conference on Automatic Face and Gesture Recognition, Grenoble, France. |
Pavlovic et al., “Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review”, Jul. 1997, pp. 677-695, vol. 19, No. 7, IEEE Transactions on Pattern Analysis and Machine Intelligence. |
Azarbayejani et al., “Visually Controlled Graphics”, Jun. 1993, vol. 15, No. 6, IEEE Transactions on Pattern Analysis and Machine Intelligence. |
Granieri et al., “Simulating Humans in VR”, The British Computer Society, Oct. 1994, Academic Press. |
Brogan et al., “Dynamically Simulated Characters in Virtual Environments”, Sep./Oct. 1998, pp. 2-13, vol. 18, Issue 5, IEEE Computer Graphics and Applications. |
Fisher et al., “Virtual Environment Display System”, ACM Workshop on Interactive 3D Graphics, Oct. 1986, Chapel Hill, NC. |
“Virtual High Anxiety”, Tech Update, Aug. 1995, pp. 22. |
Sheridan et al., “Virtual Reality Check”, Technology Review, Oct. 1993, pp. 22-28, vol. 96, No. 7. |
Stevens, “Flights into Virtual Reality Treating Real World Disorders”, The Washington Post, Mar. 27, 1995, Science Psychology, 2 pages. |
“Simulation and Training”, 1994, Division Incorporated. |
Ringbeck, et al., “A 3D Time of Flight Camera for Object Detection”, Retrieved at <<http://www.ifm-electronic.com/obj/O1D—Paper-PMD.pdf >>, Optical 3-D Measurement Techniques, Jul. 12, 2007, pp. 10. |
Kawakita, et al., “Axi-Vision Camera ˜real-time distance-mapping camera!”, Retrieved at <<http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.113.2293&rep=rep1&type=pdf >>,Aug. 1, 2000 vol. 39, No. 22 Applied Optics, pp. 3931-3939. |
State Intellectual Property Office of China, Office Action of Chinese Patent Application No. 201110431512.X, dated Sep. 23, 2013, 13 pages. |
Number | Date | Country | |
---|---|---|---|
20120154573 A1 | Jun 2012 | US |