Layered models for context awareness

Data processing: structural design – modeling – simulation – and em – Simulating electronic device or electrical system – Software program

Reexamination Certificate

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C715S708000, C715S713000, C715S861000, C706S016000, C706S020000, C706S021000, C706S022000, C345S156000, C345S158000

Reexamination Certificate

active

10183774

ABSTRACT:
The present invention relates to a system and methodology providing layered probabilistic representations for sensing, learning, and inference from multiple sensory streams at multiple levels of temporal granularity and abstraction. The methods facilitate robustness to subtle changes in environment and enable model adaptation with minimal retraining. An architecture of Layered Hidden Markov Models (LHMMs) can be employed having parameters learned from stream data and at different periods of time, wherein inferences can be determined relating to context and activity from perceptual signals.

REFERENCES:
patent: 4742558 (1988-05-01), Ishibashi et al.
patent: 5294792 (1994-03-01), Lewis et al.
patent: 5493692 (1996-02-01), Theimer et al.
patent: 5544321 (1996-08-01), Theimer et al.
patent: 5555376 (1996-09-01), Theimer et al.
patent: 5603054 (1997-02-01), Theimer et al.
patent: 5611050 (1997-03-01), Theimer et al.
patent: 5684924 (1997-11-01), Stanley et al.
patent: 5774357 (1998-06-01), Hoffberg et al.
patent: 5799132 (1998-08-01), Rizzotto et al.
patent: 5822465 (1998-10-01), Normile et al.
patent: 5842194 (1998-11-01), Arbuckle
patent: 5902968 (1999-05-01), Sato et al.
patent: 5960124 (1999-09-01), Taguchi et al.
patent: 6044343 (2000-03-01), Cong et al.
patent: 6081261 (2000-06-01), Wolff et al.
patent: 6092045 (2000-07-01), Stubley et al.
patent: 6151574 (2000-11-01), Lee et al.
patent: 6370504 (2002-04-01), Zick et al.
patent: 6466232 (2002-10-01), Newell et al.
patent: 6513046 (2003-01-01), Abbott, III et al.
patent: 6549915 (2003-04-01), Abbott, III et al.
patent: 6556960 (2003-04-01), Bishop et al.
patent: 6563503 (2003-05-01), Comair et al.
patent: 6570555 (2003-05-01), Prevost et al.
patent: 6655963 (2003-12-01), Horvitz et al.
patent: 6747675 (2004-06-01), Abbott et al.
patent: 6752317 (2004-06-01), Dymetman et al.
patent: 6791580 (2004-09-01), Abbott et al.
patent: 6801223 (2004-10-01), Abbott et al.
patent: 6812937 (2004-11-01), Abbott et al.
patent: 6842877 (2005-01-01), Robarts et al.
patent: 6950796 (2005-09-01), Ma et al.
patent: 7098891 (2006-08-01), Pryor
patent: 2001/0038711 (2001-11-01), Williams et al.
patent: 2001/0040590 (2001-11-01), Abbott et al.
patent: 2001/0040591 (2001-11-01), Abbott et al.
patent: 2001/0043231 (2001-11-01), Abbott et al.
patent: 2001/0043232 (2001-11-01), Abbott et al.
patent: 2002/0020750 (2002-02-01), Dymetman et al.
patent: 2002/0032689 (2002-03-01), Abbott, III et al.
patent: 2002/0044152 (2002-04-01), Abbot, III et al.
patent: 2002/0052930 (2002-05-01), Abbott et al.
patent: 2002/0052963 (2002-05-01), Abbott et al.
patent: 2002/0054130 (2002-05-01), Abbott, III et al.
patent: 2002/0054174 (2002-05-01), Abbott et al.
patent: 2002/0059159 (2002-05-01), Cook
patent: 2002/0078204 (2002-06-01), Newell et al.
patent: 2002/0080155 (2002-06-01), Abbott et al.
patent: 2002/0080156 (2002-06-01), Abbott et al.
patent: 2002/0083025 (2002-06-01), Robarts et al.
patent: 2002/0083158 (2002-06-01), Abbott et al.
patent: 2002/0087525 (2002-07-01), Abbott et al.
patent: 2002/0099817 (2002-07-01), Abbott et al.
patent: 2003/0046401 (2003-03-01), Abbott et al.
patent: 2003/0112987 (2003-06-01), Nordqvist et al.
patent: 2003/0154476 (2003-08-01), Abbott, III et al.
patent: 2004/0083013 (2004-04-01), Tolley
patent: 2005/0033573 (2005-02-01), Hong et al.
patent: 2005/0034078 (2005-02-01), Abbott et al.
patent: 2005/0090911 (2005-04-01), Ingargiola et al.
patent: 2005/0124863 (2005-06-01), Cook
patent: 2005/0228763 (2005-10-01), Lewis et al.
patent: 9800787 (1998-01-01), None
Shai Fine, Yoram Singer, and Naftali Tishby, The Hierarchical Hidden Markov Model:Analysis and Applications, 1998,Machine Learning.
Somboon Hongeng, Francois Bremond, and Rakant Nevatia, Representation and Optimal Recognition of Human Activties,Mar. 2000,Institute for Robotics and Intelligent Systems,pp. 1-8.
Somboon Hongeng, Francois Bremond, and Ramakant Nevatia, “Representation and Optimal Recognition of Human Activities”, Institute for Robotics and Intelligent Systems, University of Southern California, Mar. 2000, pp. 1-8 and extra one page showing the creation of the PDF.
Shai Fine, Yoram Singer, and Naftali Tishby, “The Hierarchical Hidden Markov Model: Analysis and Applications”, Machine Learning, 1998, total pages of 13.
S. Fine, Y. Singer, and N. Tishby, “The Hierarchical Hidden Markov Model”. 1998.
S. Hongeng, F. Bremond, and R. Nevatia, “Representation and Optimal Recognition of Human Activities”. Mar. 17, 2000.
N. M. Oliver, B. Rosario, and A. P. Pentland, “A Bayesian Computer Vision System for Modeling Human Interactions”. Aug. 2000 IEEE.
S. E. George, “Spatio-Temporal Analysis with the Self-Organizing Feature Map”. Knowledge and Information Systems. May 2000.
A. Dolamis, and G. Tziritas, “Adaptable Neural Networks for Content-based Video Adaptation in Low/Variable Bandwidth Communications Networks”. PDF file created on Feb. 2, 2006.
G. Potamianos, C. Neti, G. Gravier, A. Garg, and Andrew W.,“Recent Advances in the Automatic Recognition of Audio-Visual Speech”. IEEE. vol. 91. No. 9. Sep. 2003.
R. Battiti, A. Villani, and T. L. Nhat, “Neural network models for intelligent networks: deriving the location from signal patterns”.PDF file created on Apr. 29, 2002.
D. Zhang, and Dan Ellis, “Detecting sound events in basketball video archive”. PDF file created on Apr. 30, 2001.
E. Horvitz, “Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing.” Intelligent System. Sep./Oct. 1999 IEEE.
Event Structure in Perception and Conception, Psychological Bulletin 2001 vol. 127, 21 pages By: Jeffery M. Zacks & Barbara Tversky.
Recognition and Interpretation of Parametric Gesture, M.I.T. Media Laboratory Perceptual Computing Section Technical Report No. 421, Submitted to: International Conference on Computer Vision, 1998, 9 pages, By: Andrew D. Wilson and Aaron F. Bobick.
Real-Time American Sign Language Recognition from Video Using Hidden Markov Models, M.I.T. Media Laboratory Perceptual Computing Section Technical Report No. 375, An earlier version appeared ISCV 1995, 7pages, By: Thad Starner and Alex Pentland.
A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition, Proceeding of the IEEE, vol. 77, No. 2, Feb. 1989, 29 pages, By: Lawrence R. Rabiner, Fellow, IEEE.
A Bayesian Approach to Human Activity Recognition, *This research was supported in part by the Army Research Office under contracts DA AH04-95-1-0494 and DAAG55-98-1-0230, and by the Texas Higher Education Coordination Board, Advanced Research Project 97-ARP-275, 8 pages, By: Anant Madabhushi and J.k. Aggarwal.
Judging People's Availability for Interaction from Video Snapshots, 1999 IEEE, Published in the Proceedings of the Hawaii International Conference On Systems Science, Jan. 5-8, 1999, 9 pages By: Brad Johnson and Saul Greenberg.
Recognition of Visual Activities and Interactions by Stochastic Parsing, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, No. 8, Aug. 2000, 20 pages, By: Yuri A. Ivanov and Aaron F. Bobick.
A Framework for Recognizing Multi-Agent Action from Visual Evidence, M.I.T. Media Laboratory Perceptual Section Technical Report No. 489, Apr. 1999, Appears in Proceedings of the National Conference on Artifical Intelligence (AAAI), Jul. 1999,7 pages, By: Stephen S. Intille and Aaron F. Bobick.
Towards Perceptual Intelligence: Statistical Modeling of Human Individual and Interactive Behavior, Submitted to the Program in Media Arts and Sciences School of Architecture and Planning in the Partial Fulfillment of the Requirements for the Degree of Doctor Of Philosophy at the Massachusetts Insitiute of Technology, Jun. 2000, 297 pages, By; Nuria M. Oliver.
Principles of Mixed-Initiative User Interfaces, Microsoft Research, Redmond, Washington 98025 USA, 8 pages, By: Eric Horvitz.
Automatic Symbolic Traffic Scene Analysis Using Belief Networks, Computer Science Division University o

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