Visual tracking using depth data

Details Visual tracking using depth data Visual tracking using depth data

2008-05-13

2008-05-13

Bella, Matthew C. (Department: 2624)

Image analysis

Applications

Target tracking or detecting

Reexamination Certificate

active

07372977

ABSTRACT:
Real-time visual tracking using depth sensing camera technology, results in illumination-invariant tracking performance. Depth sensing (time-of-flight) cameras provide real-time depth and color images of the same scene. Depth windows regulate the tracked area by controlling shutter speed. A potential field is derived from the depth image data to provide edge information of the tracked target. A mathematically representable contour can model the tracked target. Based on the depth data, determining a best fit between the contour and the edge of the tracked target provides position information for tracking. Applications using depth sensor based visual tracking include head tracking, hand tracking, body-pose estimation, robotic command determination, and other human-computer interaction systems.

REFERENCES:
patent: 5454043 (1995-09-01), Freeman
patent: 5581276 (1996-12-01), Cipolla et al.
patent: 5594469 (1997-01-01), Freeman et al.
patent: 6002808 (1999-12-01), Freeman
patent: 6057909 (2000-05-01), Yahav et al.
patent: 6128003 (2000-10-01), Smith et al.
patent: 6215890 (2001-04-01), Matsuo et al.
patent: 6278798 (2001-08-01), Rao
patent: 6674904 (2004-01-01), McQueen
patent: 6720949 (2004-04-01), Pryor et al.
patent: 6788809 (2004-09-01), Grzeszczuk et al.
patent: 6819782 (2004-11-01), Imagawa et al.
patent: 7203356 (2007-04-01), Gokturk et al.
patent: 2002/0041327 (2002-04-01), Hildreth et al.
patent: 2002/0181773 (2002-12-01), Higaki et al.
patent: 2003/0113018 (2003-06-01), Nefian et al.
patent: 2003/0156756 (2003-08-01), Gokturk et al.
patent: 2004/0151366 (2004-08-01), Nefian et al.
patent: 2004/0189720 (2004-09-01), Wilson et al.
patent: 2004/0193413 (2004-09-01), Wilson et al.
patent: 2005/0265583 (2005-12-01), Covell et al.
patent: 2006/0033713 (2006-02-01), Pryor
patent: WO 00/30023 (2000-05-01), None
patent: WO 2004/097612 (2004-11-01), None
Ahlberg, J., “Using The Active Appearance Algorithm For Face And Facial Feature Tracking”,Proc. 2ndInt. Workshop Recognition, Analysis, and Tracking Of Faces And Gestures In Realtime Systems(RATFFG-RTS), pp. 68-72, 2001.
Beymer, David J., “Face Recognition Under Varying Pose”,A.I .Memo No. 1461, Artificial Intelligence Laboratory, MIT 1993.
Birchfeld, S., “An Elliptical Head Tracker”,Proc.31stAsilomar Conf. Signals, Systems, and Computers, 1997.
Cascia, M.L., Sclaroff, S., and Athitsos, C., “Fast Reliable Head Tracking Under Varying Illumination: An Approach Based On Registration Of Texture-Mapped 3D Models”,IEEE Trans. on PAMI, vol. 22, No. 4, pp. 322-336, 2000.
Comaniciu, D. and Meer, P., “Mean Shift: A Robust Approach Toward Feature Space Analysis”,IEEE Trans. On PAMI, vol. 24, No. 5 pp. 1-18, 2002.
Edwards, J., Taylor, C.J., and Cootes, T.F., “Learning To Identify And Track Faces In Image Sequences”,In Proceeding Of The International Conference On Face And Gesture Recognition, pp. 260-265, 1998.
Feris, R. S., Cesar Jr., R.M., “Tracking Facial Features Using Gabor Wavelet Networks”,Proc. Brazilian Conference On Computer Graphics, Image Processing -Sibgrapi00, IEEE Computer Society Press, pp. 22-27, 2000.
Fukunaga, K., “Introduction To Statistical Pattern Recognition”, Academic Press, 1990.
Gee and Cipola, “Determining The Gaze Of Faces In Images”,Image and Vision Computing, vol. 12, No. 10, pp. 639-647, 1994.
Henry, M.H., Lakshmann, S. and Watta, P., “Optical Flow Prepossessing For Pose Classification And Transition Recognition Using Class-Specific Principle Component Analysis”, Proc. Of IEEE Intelligent Vehicles Symposium, Jun. 2003, Columbus OH 604-609.
Huang, K.S., Trevedi, M.M. and Gandhi, T., “Driver's View And Vehicle Surround Estimation Using Omnidirectional Video Stream”, Proc. Of IEEE Intelligent Vehicles Symposium, Jun. 2003, Columbus OH, 444-449.
Huttenlocher, D., Klanderman, G and Rucklidge, W.J., “Comparing Images Using The Hausdorff Distance”,IEEE Transactions On Pattern Analysis And Machine Intelligence15(9):850-863, 1993.
Iddan, G.J. and Yahav, G. “3D Imaging In The Studio”,SPIE, vol. 4298, pp. 48, Apr. 2001.
Ji, Q. and Yang, X., “Real Time 3D Face Pose Discrimination Based On Active IR Illumination”,Int. Conf. On Pattern Recognition, pp. 310-313, 2002.
Kamiji, K., Kawamura, N., “Study Of Airbag Interference With Out Of Position Occupant By the Computer Simulation”, 2000.
Krueger, V., Bruns, S. and Sommer, G., “Efficient Head Pose Estimation With Gabor Wavelet Networks”,BMVC, 2000.
Malciu, M., Prteux, F., “A Robust Model-Based Approach For 3D Head Tracking In Video Sequences”,International Conference On Automatic Face And Gesture Recognition, 2000.
McKenna, S.J., Raja, Y., and Gong, S., “Object Tracking Using Adaptive Colour Mixture Models”,Lecture Notes in Computer Science, 1998.
Moller, M. F., “A Scaled Conjugate Gradient Algorithm For Fast Supervised Learning”,Neural Networks, vol. 6, pp. 525-533, 1993.
Morency, L.P., Rahimi, A., Checka, N., Darrell, T., “Fast Stereo-Based Head Tracking For Interactive Environments”,Face and Gesture, 2002.
Neflan, A.V. and Hayes, III, M.H., “Face Detection And Recognition Using Hidden Markov Models”,proc. IEEE Int'l. Conf. Image Processing, vol. 1, pp. 141-145, 1998.
Nishihara, H.K., Huber, Thomas, H.J., Huber, E., “Real-Time Tracking Of People Using Stereo And Motion”,SPIE Proceedings, vol. 2183, pp. 266-273, 1994.
Osuna, E., Freund, R., and Girosi, F., “Training Support Vector Machines: An Application To Face Detection”,Proc. IEEE Computer Society Conf. Computer Vision And Pattern Recognition, pp. 130-136, 1997.
Pappu, R., Beardsley, P.A., “Qualitative Approach To Classifying Gaze Direction”,International Conference On Automatic Face And Gesture Recognition, 1998.
Pardas, M., Sayrol, E., “A New Approach To Tracking With Active Contours”,Proceedings. 2000 International Conference of Image Processing, vol. 2, pp. 259-262, 2000.
Potzsch, M., Kruger, N. and von der Malsburg, C., “Determination Of Face Position And Pose With A Learned Representation Based On Labeled Graphs, Image And Vision Computing” vol. 15, No. 8, pp. 665-673, 1997.
Rowley, H.A., Baluja, S., and Kanade, T., “Neural Network-Based Face Detection”,IEEE Trans. Pattern Analysis And Machine Intelligence, vol. 20, No. 1, pp. 23-28, Jan. 1998.
Russaknoff, D., and Herman, M., “Head Tracking Using Stero”,Machine Vision And Application, vol. 13, pp. 164-173, 2002.
Sako, H., et al., “Real-Time Facial-Feature Tracking Based On Matching Techniques And Its Applications”,Proceedings of The 12thIAPR International Conference On Pattern Recognition, pp. 320-324, 1994.
Shao, X., Huang, J., Li, D., and Weschler, H., “Pose Discrimination And Eye Detection Using Support Vector Machines”, Proc. of 14thInternational Conference on Pattern Recognition, 1998.
Srinivasan, S., and Boyer, K., “Head Pose Estimation Using View Based Eigenspaces”,Int. Conf. On Pattern Recognition, pp. 302-305, 2002.
Stiefelhagen, R., Finke, M., Yang, J. Waibel, A., “From Gaze To Focus Of Attention”,Lecture Notes In Computer Science, vol. 1614, pp. 761-768, Jun. 1999.
Stiefelhagen, R., Yang, J., Waibel, A., “Tracking Focus Of Attention For Human-Robot Communication”,International Conference On Humanoid Robots, 2001.
Sung, K.K., and Poggio, T., “Example—Based Learning For View-Based Human Face Detection”,IEEE Trans. On Pattern Analysis And Machine Intelligence, vol. 20, No. 1, pp. 39-51, Jan. 1998.
Takemura, K., Ido, J., Matusmoto, Y., Ogasawara, T., “Drive Monitoring System Based On Non-Contact Measurement System Of Driver's Focus Of Visual Attention”, Proc. Of IEEE Intelligent Vehicles Symposium, Jun. 2003, Columbus OH, 581-586.
Wechsler, H., “Face Recognition: Fro

Affiliated with

Also associated with

Rating

Visual tracking using depth data does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Visual tracking using depth data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Visual tracking using depth data will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-2798872