Image analysis – Applications – Target tracking or detecting
Reexamination Certificate
2011-08-23
2011-08-23
Carter, Aaron W (Department: 2624)
Image analysis
Applications
Target tracking or detecting
C382S154000, C715S863000, C379S052000
Reexamination Certificate
active
08005263
ABSTRACT:
A method and system for recognizing hand signs that include overlapping or adjoining hands from a depth image. A linked structure comprising multiple segments is generated from the depth image including overlapping or adjoining hands. The hand pose of the overlapping or adjoining hands is determined using either (i) a constrained optimization process in which a cost function and constraint conditions are used to classify segments of the linked graph to two hands or (ii) a tree search process in which a tree structure including a plurality of nodes is used to obtain the most-likely hand pose represented by the depth image. After determining the hand pose, the segments of the linked structure are matched with stored shapes to determine the sign represented by the depth image.
REFERENCES:
patent: 5454043 (1995-09-01), Freeman
patent: 5581276 (1996-12-01), Cipolla et al.
patent: 5594469 (1997-01-01), Freeman et al.
patent: 5787197 (1998-07-01), Beigi et al.
patent: 6002808 (1999-12-01), Freeman
patent: 6128003 (2000-10-01), Smith et al.
patent: 6215890 (2001-04-01), Matsuo et al.
patent: 6720949 (2004-04-01), Pryor et al.
patent: 6788809 (2004-09-01), Grzeszczuk et al.
patent: 6804396 (2004-10-01), Higaki et al.
patent: 6819782 (2004-11-01), Imagawa et al.
patent: 6950534 (2005-09-01), Cohen et al.
patent: 7095401 (2006-08-01), Liu et al.
patent: 7224830 (2007-05-01), Nefian et al.
patent: 7274800 (2007-09-01), Nefian et al.
patent: 7308112 (2007-12-01), Fujimura et al.
patent: 7340077 (2008-03-01), Gokturk et al.
patent: 7372977 (2008-05-01), Fujimura et al.
patent: 7379563 (2008-05-01), Shamaie
patent: 2002/0041327 (2002-04-01), Hildreth et al.
patent: 2004/0189720 (2004-09-01), Wilson et al.
patent: 2004/0193413 (2004-09-01), Wilson et al.
patent: 2005/0031166 (2005-02-01), Fujimura et al.
patent: 2005/0238201 (2005-10-01), Shamaie
patent: 2006/0033713 (2006-02-01), Pryor
patent: 2006/0209021 (2006-09-01), Yoo et al.
patent: 2007/0216642 (2007-09-01), Kneissler
patent: 2008/0212836 (2008-09-01), Fujimura et al.
patent: 2008/0219502 (2008-09-01), Shamaie
patent: 2009/0110292 (2009-04-01), Fujimura et al.
patent: 2010/0060576 (2010-03-01), Underkoffler et al.
patent: 2010/0066676 (2010-03-01), Kramer et al.
patent: WO 00/30023 (2000-05-01), None
patent: WO 2004/097612 (2004-11-01), None
patent: WO 2004/097612 (2004-11-01), None
Gvili, R., et al., “Depth Keying”, SPIE Elec. Imaging, 2003.
Ishibuchi et al., “Real Time Vision-Based Hand Gesture Estimatiohn for a Human-Computer Interface”, Systems and Computers in Japan, vol. 28, No. 7, 1997.
Redert et al., “ATTEST: Advanced Three-dimensional Television System technologies”, Proceedings of the First International Symposium on 3D Data Processing Visualization and Transmission (3DPVT02), 2002.
Zhu et al., “3D Head Pose Estimation with Optica Flow and Depth Constraints”, Proceedings of the Fourth International Conference on 3D Digital Imaging and Modeling, 2003.
Athitsos, V. et al., “An Appearance-Based Framework for 3D Hand Shape Classification and Camera Viewpoint Estimation,” Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition (FGR'02), IEEE, 2002, 8 pages.
Bretzner, L. et al., “Hand Gesture Recognition using Multi-Scale Colour Features, Hierarchical Models and Particle Filtering,” Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition (FGR'02), IEEE, 2002, 8 pages.
Gavrila, D.M. et al., “Real-Time Object Detection for “Smart” Vehicles,” The Proceedings of the Seventh IEEE International Conference on Computer Vision, Sep. 20-27, 1999, 10 pages.
Iddan, G.J. et al., “3D Imaging in the Studio (and Elsewhere . . . )” Proceedings of the SPIE, Jan. 24-25, 2001, pp. 48-55, vol. 4298.
Jojic, N. et al., “Detection and Estimation of Pointing Gestures in Dense Disparity Maps,” Fourth IEEE International Conference on Automatic Face and Gesture Recognition, Mar. 28-30, 2000, 15 pages.
Malassiotis, S. et al., “A Gesture Recognition System using 3D Data,” Proceedings of the First International Symposium on 3D Data Processing Visualization and Transmission (3DPVT'02), IEEE, 2002, pp. 1-4.
Oka, K. et al., “Real-Time Tracking of Multiple Fingertips and Gesture Recognition for Augmented Desk Interface System,” Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition (FGR'02), IEEE, 2002, 12 pages.
Pavlovic, V.I. et al., “Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Jul. 1997, vol. 17, No. 7.
Polat, E. et al., “Robust Tracking of Human Body Parts for Collaborative Human Computer Interaction,” Computer Vision and Image Understanding, 2003, pp. 44-69, vol. 89.
Sakagami, Y. et al., “The Intelligent ASIMO: System Overview and Integration,” Proceedings of the 2002 IEEE/RSJ, Intl. Conference on Intelligent Robots and Systems, IEEE, 2002, pp. 2478-2483.
Starner, T. et al., “Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Dec. 1996, pp. 1371-1375, vol. 20, No. 12.
Vogler, C. et al., “ASL Recognition Based on a Coupling Between HMMs and 3D Motion Analysis,” Sixth International Conference on Computer Vision, Jan. 4-7, 1998, pp. 363-369.
Wilson, A.D. et al., “Parametric Hidden Markov Models for Gesture Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Sep. 1999, pp. 884-900, vol. 21, No. 9.
Zhu, X. et al., “Segmenting Hands of Arbitrary Color,” Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition, Mar. 28-30, 2000, pp. 446-453.
Zhu, Y., et al., “A Real-Time Approach to the Spotting, Representation, and Recognition of Hand Gestures for Human-Computer Interaction,” Computer Vision and Image Understanding, 2002, pp. 189-208, vol. 85.
Lee et al., “Online, Interactive Learning of Gestures for Human/Robot Interfaces,” Proceedings of the 1996 IEEE International Conference on Robotics and Automation, Apr. 1996, pp. 2982-2987.
PCT International Search Report and Written Opinion, PCT/US08/75276, Nov. 13, 2008.
Teófilo Emidio De Campos, 3DVisual Tracking of Articulated Objects and Hands, Robotics Research Group, Department of Engineering Science, University of Oxford, Trinity Term 2006, pp. 1-212, England.
Eun-Jung Holden et al,Visual Sign Language Recognition, [online], [Retrieved on Feb. 5, 2008], pp. 1-5, Retrieved from the URL: http://www.postgraduate.uwa.edu.au/about/PVCR/publications?f=147693.
F. Le Jeune et al,Tracking of Hand's Posture and Gesture, [online], [Retrieved on Feb. 5, 2008, dated Oct. 2004], pp. 1-26, Retrieved from the URL:http://www.enpc.fr/certis/publications/papers/04certis02.pdf.
Ronen Gvili et al,Depth keying, 3DV Systems Ltd., pp. 1-11, 2003.
Claudia Nölker et al,Visual Recognition of Continuous Hand Postures, [online], [Retrieved on Feb. 5, 2008], pp. 155-178, Retrieved from the URL: http://www.phonetik.uni-muenchen.de/FIPKM/vol37/hamp—noelker.pdf.
Thad Eugene Starner,Visual Recognition of American Sign Language Using Hidden Markov Models, [online], [Retrieved on Feb. 5, 2008, dated Feb. 1995], pp. 1-52, Retrieved from the URL: http://citeseer.ist.psu.edu/124187.htm.I.
Jochen Triesch et al,Classification of hand postures against complex backgrounds using elastic graph matching, Image and Vision Computing, Jul. 11, 2002, pp. 937-943, vol. 20.
Fujimura Kikuo
Xu Lijie
Carter Aaron W
Duell Mark E.
Fenwick & West LLP
Honda Motor Co. Ltd.
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