Data processing: artificial intelligence – Knowledge processing system – Knowledge representation and reasoning technique
Reexamination Certificate
2005-09-06
2005-09-06
Knight, Anthony (Department: 2121)
Data processing: artificial intelligence
Knowledge processing system
Knowledge representation and reasoning technique
C706S045000
Reexamination Certificate
active
06941290
ABSTRACT:
A method for computing all occurrences of a compound event from occurrences of primitive events where the compound event is a defined combination of the primitive events. The method includes the steps of: (a) defining primitive event types; (b) defining combinations of the primitive event types as a compound event type; (c) inputting the primitive event occurrences, such occurrences being specified as the set of temporal intervals over which a given primitive event type is true; and (d) computing the compound event occurrences, such occurrences being specified as the set of temporal intervals over which the compound event type is true, where the sets of temporal intervals in steps (c) and (d) are specified as smaller sets of spanning intervals, each spanning interval representing a set of intervals.
REFERENCES:
patent: 3647978 (1972-03-01), Hill
patent: 5153922 (1992-10-01), Goodridge
patent: 5301320 (1994-04-01), McAtee et al.
patent: 5966523 (1999-10-01), Uchino
patent: 6021403 (2000-02-01), Horvitz et al.
patent: 6424370 (2002-07-01), Courtney
patent: 6785663 (2004-08-01), Wang et al.
patent: 6813312 (2004-11-01), Tullberg et al.
Kerridge et al; Synchronization Primitives for Highly Parallel Discrete Event Simulations; Proceedings of the 32nd Annual Hawaii International Conference on System Sciences; vol. Track 8; Jan. 5-8, 1999; pp 1-10.
Siskind; Grounding Language in Perception; Artificial Intelligence Review; vol. 8; Dec. 1994; pp 371-391.
Allen; Maintaining Knowledge About Temporal Intervals; Communications of the ACM; vol. 26, Iss. 1; Nov. 1983; pp 832-843.
Chow; A Generalized Assertion Language; Proceedings of the 2nd International Conference on Software Engineering; Oct. 1976.
Thiele et al; On Fuzzy Temporal Logic; Second IEEE International Conference on Fuzzy Systems; vol. 2; Mar. 28-Apr. 1, 1993; pp 1027-1032.
Abe. N. et al., “A Plot Understanding System on Reference to Both Image and Lanaguge,” Proceedings of the Seventh International Joint Conference on Artificial Intelligence, Vancouver, Canada, pp. 77-84, Aug. 1981.
Abe, N. et al., “A Learning of Object Structures by Verbalism,” COLING 82, pp. 1-8, 1982.
Adler, M.R., “Computer Interpretation of Peanuts Cartoons,” 5th International Joint Conference on Artificial Intelligence, Cambridge, MA, pp. 608, Aug. 1977.
Allen, J.R., “Maintaining Knowledge About Temporal Intervals,” Communications of the ACM, vol. 26, No. 11, pp. 832-843, Nov. 1983.
Blum, M. et al., “A Stability Test for Configurations of Blocks,” Artificial Intelligence Memo No. 168, Massachusetts Institute of Technology, Feb. 1970.
Bobick, A.F. et al., “Action Recognition using Probabilistic Parsing,” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 196-202, Jun. 1998.
Borchardt, G.C., “A Computer Model for the Representation and Identification of Physical Events,” Masters Thesis, University of Kansas, May 1984.
Borchardt, G.C., “Events Calculus,” Proceedings of the Ninth International Joint Conference on Artificial Intelligence, pp. 524-527, Aug. 1985.
Brand, M. et al., “Sensible Scenes: Visual Understanding of Complex Structures Through Causal Analysis,” Proceedings of the Eleventh National Conference on Artificial Intelligence, pp. 588-593, 1993.
Fahlman, S.E., “A Planning System for Robot Construction Tasks,” Artificial Intelligence, vol. 5, No. 1, pp. 1-49, 1974.
Krifka, M., “Thematic Relations as Links Between Nominal Reference and Temporal Constitution,” Lexical Matters, Sag, I.A. (eds.), pp. 29-53, 1992.
Mann, R. et al., “Towards the Computational Perception on Action,” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Santa Barbara, CA, pp. 794-799, 1998.
Mann, R. et al., “The Computational Perception of Scene Dynamics,” Computer Vision and Image Understanding, vol. 65, No. 2, pp. 113-128, Feb. 1997.
McCarthy, J., “Circumscription—A Form of Non-Monotonic Reasoning,” Artificial Intelligence, vol. 13, pp. 27-39, 1980.
Okada, N., “SUPP: Understanding Moving Picture Patterns Based on Linguistic Knowledge,” Proceedings of the Sixth International Joint Conference on Artificial Intelligence, Tokyo, Japan, pp. 690-692, Aug. 1979.
Regier, T.P., “The Acquisition of Lexical Seminatics for Spatial Terms: A Connectionist Model of Perceptual Categorization,” Ph.D. Thesis, University of California, Berkeley, 1992.
Shoham, Y., “Temporal Logics in Al: Semantical and Ontological Considerations,” Artificial Intelligence, vol. 33, pp. 89-104, 1987.
Siskind, J.M., “Naive Physics, Event Perception, Lexical Semanics, and Language Acquisition,” Ph.D. Thesis, Massachusetts Institute of Technology, 1992.
Siskind, J.M., “Axiomatic Support for Event Perception,” Proceedings of the AAAI-94 Workshop on the Integration of Natural Language and Vision Processing. Seattle, WA, pp. 153-160, Aug. 1994.
Siskind, J.M., “Grounding Language in Perception,” Artificial Intelligence Review, vol. 8, pp. 371-391, Dec. 1994.
Siskind, J.M., “Unsupervised Learning of Visually-Observed Events,” AAAI Fall Symposium Series on Learning Complex Behaviors in Adaptive Intelligence Systems, pp. 82-83, 1996.
Siskind, J.M., “Visual Event Perception”, Proceedings of the 9th NEC Research Symposium, Princeton, NJ, Mar. 1999.
Siskind, J.M., “Visual Event Classification via Force Dynamics,” Proceedings of the Seventeenth National Conference on Artificial Intelligence, Aug. 2000.
Siskind, J.M. et al., “A Maximum-Likelihood Approach to Visual Event Classification,” Proceedings of the 4th European Conference on Computer Vision, Cambridge, UK, pp. 347-360, Apr. 1996.
Starner, T.E., “Visual Recognition of American Sign Language Using Hidden Markov Models,” Masters Thesis, Massachusetts Institute of Technology, Feb. 1995.
Talmy, L., “Force Dynamics in Language and Cognition,” Cognitive Science, vol. 12, pp. 49-100, 1988.
Thibadeau, R., “Artificial Perception of Actions,” Cognitive Science, vol. 10, No. 2, pp. 117-149, 1986.
Tsuji, S. et al., “Understanding a Simple Cartoon Film by a Computer Vision System,” Proceedings of the 5th International Joint Conference on Artificial Intelligence, Cambridge MA, pp. 609-610, Aug. 1977.
Tsuji, S. et al., “Three Dimensional Movement Analysis of Dynamic Line Images,” Proceedings of the Sixth International Joint Conference on Artificial Intelligence, Tokyo, Japan, pp. 896-901, Aug. 1979.
Tsuji, S. et al., “Tracking and Segmentation of Moving Objects in Dynamic Line Images,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 2, No. 6, pp. 516-522, 1980.
Waltz, D.L., “Toward a Detailed Model of Processing for Language Describing the Physical World,” Proceedings of the Seventh International Joint Conference on Artificial Intelligence, Vancouver, Canada, pp. 1-6, Aug. 1981.
Waltz, D.L., “Visual Analog Representations for Natural Language Understanding,” Proceedings of the Sixth International Joint Conference on Artificial Intelligence, Tokyo, Japan, pp. 926-934, Aug. 1979.
Yamato, J. et al., “Recognizing Human Action in Time-Sequential Images using Hidden Markov Model,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 379-385, 1992.
Chow; A Generalized Assertion Language; Proceedings of the 2nd International Conference on Software Engineering; Oct. 1976; pp 392-399.
Thiele et al; On Fuzzy Temporal Logic; Second IEEE International Conference on Fuzzy Systems', vol. 2., Mar. 28-Apr 1, 1993., pp 1027-1032.
Kerridge et al; Synchronization Primitives for Highly Parallel Discrete Event Simulations', Proceedings of the 32nd Annual Hawaii International Conference on System Sciences,
Bell Meltin
Knight Anthony
NEC Laboratories America, Inc.
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