Scaleable object recognition with a belief model

Data processing: artificial intelligence – Knowledge processing system – Knowledge representation and reasoning technique

Reexamination Certificate

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C382S123000

Reexamination Certificate

active

09881746

ABSTRACT:
An exemplary embodiment of the present invention is directed to a system, method and computer program product for providing an object recognition blackboard system architecture. The system for recognizing objects in content can include: a blackboard comprising a plurality of experts, and data comprising original input data and data created by processing of any of the plurality of experts, and a controller operative to control the experts; a belief model, coupled to the controller, comprising a set of beliefs and probabilities associated with each belief of the set of beliefs; a belief network, coupled to the controller; and a relations subsystem, coupled to the controller.

REFERENCES:
patent: 5032525 (1991-07-01), Lee et al.
patent: 5418888 (1995-05-01), Alden
patent: 5448502 (1995-09-01), Kindo et al.
patent: 5448722 (1995-09-01), Lynne et al.
patent: 5701400 (1997-12-01), Amado
patent: 5787234 (1998-07-01), Molloy
patent: 5974549 (1999-10-01), Golan
patent: 6058206 (2000-05-01), Kortge
patent: 6571013 (2003-05-01), Macey et al.
patent: 6671818 (2003-12-01), Mikurak
patent: 2002/0083333 (2002-06-01), Frank et al.
W.-C. Lin, S.Y. C.-T. Chen; “Dempster-Shafer Reasoning for Medical Image Recognition”;Proceedings of the 1991 IEEE Third International Conference on Tools for Artificial Intelligence; TAI '91; Nov. 10-13, 1991; pp. 480-487□□.
W. Elliot, Dr. M. Schneider; “Fault Finder”;Proceedings of the 1990 ACM SIGSMALL/PC symposium on Small systems; Feb. 1990; pp. 13-23.
S.-Y Chen, W.-C. Lin, C.-T. Chen; “Spatial reasoning based on multivariate belief functions”; 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Proceedings CVPR '92; Jun. 15-18, 1992; pp. 624-626.
Ng et al; Consensus in a multi-expert system; 1990 ACM annual Proceedings conference on Cooperation; Jan. 1990.
Papadias et al; Special issue on spatial database systems; Qualitative representation of spatial knowledge in two-dimensional space; The VLDB Journal; Oct. 1994; vol. 3 Is. 4.
Wang et al; Logical design for temporal databases with multiple granularities; ACM Transactions on Database Systems; vol. 22, Is. 2; Jun. 1997.
von Collani et al; A general learning approach to multisensor based control using statistic indices; IEEE Int'l Conference on Robotics and Automation, 2000 vol. 4; Apr. 24-28, 2000; pp. 3221-3226.
De Natale et al; Interpretation of underwater scene data acquired by a 3-D acoustic camera; IEEE International Conference on Acoustics, Speech, and Signal Processing; vol. 2; Mar. 23-26, 1992; pp. 485-488.
Tsukamoto et al; A methodological approach on real-time gesture recognition using multiple silhouette models; Proceedings 4th IEEE International Workshop on Robot and Human Communication; Jul. 5-7, 1995; pp. 123-128.
Pearl; Decision making under uncertainty; ACM Computing Surveys; vol. 28, Is. 1; Mar. 1996; pp. 89-92.
Elliott et al; “Fault Finder”; Proceedings of the 1990 ACM SIGSMALL/PC symposium on Small systems; Feb. 1990; pp. 13-23.
http://wotan.liu.edu/docis/dbl/aintel/1990—42—2—3—393—TCCOPI.htm; pp. 1.
http://bayes.cs.ucla.edu/jp—home.html; Cognitive Systems Laboratory Publications; pp. 1-24.
Neapolitan; Is higher-order uncertainty needed?; IEEE Transactions on Systems, Man and Cybernetics Part A; vol. 26, Is. 3; May 1996; pp. 294-302.
Watson; Blackboard Architectures and Applications review; SIGART Bulletin, vol. 1, No. 3; pp. 19-20; http://delivery.acm.org/10.1145/1060000/1056294/p19-watson.pdf?key1=1056294&key2=3510618111&coll=GUIDE&dl=GUIDE&CFID=46756301&CFTOKEN=38049324.
Pearl; Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference; Morgan Kaufman; 1988; pp. vii-xix.
Jagannathan et al; Blackboard Architecture and Applications; Academic Press, Inc.; 1989; pp. vii-xvii.
Neapolitan; Probabilistic Reasoning in Expert Systems Theory and Algorithms; John Wiley & Sons; 1990; pp. vii-xiii.
Cooper; The computational Complexity of Probabilistic Inference Using Bayesian Belief Networks; Artificial Intelligence; vol. 42, Is. 2-3; Mar. 1990; pp. 393-405.
Spiegelhalter; Probabilistic Reasoning in Expert Systems; American Journal of Mathematical and Management Sciences; vol. 9, Is. 3-4; 1991; pp. 191-210.
Ng et al; Consensus in a multi-expert system; 1990 ACM annual Proceedings conference on Cooperation; Jan. 1990; pp. 351-357.
Papadias et al; Special issue on spatial database systems; Qualitative representation of spatial knowledge in two-dimensional space; The VLDB Journal; Oct. 1994; vol. 3 Is. 4; pp. 479-516.
Wang et al; Logical design for temporal databases with multiple granularities; ACM Transactions on Database Systems; vol. 22, Is. 2; Jun. 1997; pp. 115-170.
von Collani et al; A general learning approach to multisensor based control using statistics indices; IEEE Int'l Conference on Robotics and Automation, 2000 vol. 4; Apr. 24-28, 2000; pp. 3221-3226.
Search Report as issued by the European Patent Office (as International Searching Authority); mailed on Mar. 8, 2002 for International Application No. PCT/US01/19446; Applicant: Lockheed Martin Mission Systems, et al.
Bosschere De Kom, et al.; “Some Low-Level Issues in the Implementation of a Shared Blackboard”; Proceedings Euromicro Workshop on Parallel and Distributed Processing; Jan. 27, 1993; pp. 88-95.
M. Piaggio & A.; “A Programming Environment for Real Time Control of Distributed Multiple Robotic Systems”; Technical Report, DIST Laboratorium; Jul. 23, 1999; Online—Internet: http:\\wynona.laboratorium.dist.unige.
J. Archibald; “Flexibility in Blackboard System for Solving Dynamic Resource-Constrained Scheduling Problems”; School of Computing and Information Systems; 1996; Online—Internet: http:\\citeseer.nj.nec.com\cache\lpapers\cs\7055\.
C. Hood; “Application of Blackboard Technology to Allow Non-Linear OCR Processing”; Symposium on Document Image Understanding, 1997, XP00101033637 (entire document).
Wei-Chung et al; “Dempster-Shafer Reasoning For Medical Image Recognition”; Proceedings of the international Conference on Tolls for Artificial Intelligence, San Jose, Nov. 5-8, 1991; Los Alamitos, CA; IEEE Computer Soc, US vol. Conf. 3.
Clement V et al; “Interpretation of Remotely Sensed Images in a Context of Multisensor Fusion Using a Multispecialist Architecture”; IEEE Transactions on Geoscience and Remote Sensing, IEEE Inc., New York, US, vol. 31, No. 4, Jul. 1, 1993; pp. 779-791 XP000413026; ISSN: 0196-2892; Section: “III. A Real World Modeling” Abstract, Figure 1.
Search Report as issued by the European Patent Office (as International Searching Authority); mailed Mar. 8, 2002 for International Application No. PCT/US01/19446; Applicant: Lockheed Martin Mission Systems, et al.
C. Hood; “Application of Blackboard Technology to Allow Non-Linear OCR Processing”; Symposium on Document Image Understanding, 1997. Note to Examiner: Reference not enclosed.
Wei-Chung Lin et al.; “Dempster-Shafer Reasoning for Medical Image Recognition”; IEE Computer Society, U.S., vol.—Conference 3; Nov. 10, 1991; pp. 480-487; Los Alamitos, California. Reference not enclosed.
Clement, V., et al.; “Intrpretation of Remotely Sensed Images in a Context of Multisensor Fusion Using a Multispecialist Architecture”; IEE Transactions on Geoscience and Remote Sensing; Jul. 1, 1993; vol. 32, No. 4, pp. 779-791; New York, New York.
Bosschere De Kom, et al.; “Some Low-Level Issues in the Implementation of a Shared Blackboard”; Proceedings Euromicro Workshop on Parallel and Distributed Processing; Jan. 27, 1993; pp. 88-95.
M. Piaggio & A.; “A Programming Environment for Real Time Control of Distributed Multiple Robotic Systems”; Technical Report, DIST Laboratorium; Jul. 23, 1999; Online—Internet: http:\\wynona.laboratorium.dist.unige.
J. Archibald; “Flexibility in Blackboard

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