Image analysis – Applications – Target tracking or detecting
Reexamination Certificate
2006-12-29
2011-11-01
Koziol, Stephen (Department: 2624)
Image analysis
Applications
Target tracking or detecting
C382S100000, C382S190000
Reexamination Certificate
active
08050454
ABSTRACT:
Methods to process digital video using trajectory extraction and spatiotemporal decomposition for search and retrieval of video are described. An example method extracts interest point data from data representing a plurality of video frames. The interest point data is extracted from each of the video frames independent of the other video frames. Subsequent to extracting the interest point data, the example method links at least some of the interest point data to generate corresponding trajectory information. The example method also clusters the trajectory information to form clustered trajectory information and extracts a representative feature index from the clustered trajectory information.
REFERENCES:
patent: 6636220 (2003-10-01), Szeliski et al.
patent: 6804398 (2004-10-01), Kaneko et al.
patent: 7085401 (2006-08-01), Averbuch et al.
patent: 7200266 (2007-04-01), Ozer et al.
patent: 7840076 (2010-11-01), Bouguet et al.
patent: 2006/0066719 (2006-03-01), Haering et al.
patent: 2008/0052262 (2008-02-01), Kosinov et al.
patent: 2008/0240575 (2008-10-01), Panda et al.
Costeira and Kanade “A Muiltibody Factorization Method for Independently Moving Objects” International Journal on Computer Vision, pp.159-179, 1998.
Lowe “Distinctive Image Features from Scale-Invariant Keypoints,” European Conference on Computer Vision, pp. 128-132, 2002.
Gruber and Weiss “Incorporating Non-motion Cues into 3D Motion Segmentation” Proceedings of the European Conference on Computer Vision, May 2006.
Shi and Malik “Normalized Cuts and Image Segmentation” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22 No. 8 Aug. 2000.
“Diamond: A System for Interactive Search,” Dec. 16, 2006 [retrieved from http://replay.web.archive.org/20061216083539/http://diamond.cs.cmu.edu/ on May 5, 2011] 1 pages.
“TREC Video Retrieval Evaluation,” Sep. 30, 2006 [retrieved from http://replay.web.archive.org/20060930001855/http://www-nlpir.nist.gov/projects/trecvid/ on May 5, 2011] 2 pages.
“Espion Video Search,” Dec. 14, 2006 [retrieved from http://replay.web.archive.org/20061214085003/http://ideeinc.com/espion-video.php on May 5, 2011] 1 page.
Goode et al., “Interactive Search of Adipocytes in Large Collections of Digital Cellular Images,” Technical Report CMU-CS-06-177, School of Computer Science, Carnegie Mellon University, Dec. 2006, 16 pages.
Huston et al., “Dynamic Load Balancing for Distributed Search,” Proceedings of High Performance Distributed Computing, 2005, 10 pages.
Nizhner et al., “Network-Aware Partitioning of Computation in Diamond,” Carnegie Mellon Technical Report CMU-CS-04-148, Jun. 2004, 22 pages.
Huston et al., “SnapFind: Brute Force Interactive Image Retrieval,” Proceedings of International Conference on Image Processing and Graphics, 2004, 6 pages.
Huston et al., “Forensic Video Reconstruction,” Proceedings of International Workshop on Video Surveillance and Sensor Networks, Oct. 15, 2004, 9 pages.
Hoiem et al., “Object-Based Image Retrieval Using the Statistical Structure of Images,” Proceedings of Computer Vision and Pattern Recognition, 2004, 8 pages.
Huston et al., “Diamond: A Storage Architecture for Early Discard in Interactive Search,” Proceedings of USENIX Conference on File and Storage Technologies, 2004, 14 pages.
Veltkamp et al., “Content-Based Image Retrieval Systems: A Survey,” Utrecht University, Oct. 28, 2002, pp. 1-62.
Muller et al., “Benchmarking Image Retrieval Applications,” Proceedings of the Seventh International Conference on Visual Information Systems, San Francisco, USA, Sep. 2004, 4 pages.
Muller et al., “Performance Evaluation in Content-Based Image Retrieval: Overview and Proposals,” Technical Report 99.05, University of Geneva, Dec. 1, 1999, 12 pages.
Hauptmann et al., “Successful Approaches in the TREC Video Retrieval Evaluations,” in Proceedings of ACM Multimedia, Oct. 10-16, 2004, pp. 668-675.
Peker et al., “Low-level Motion Activity Features for Semantic Characterization of Video,” in Proceedings of IEEE International Conference on Multimedia and Expo, 2000, 4 pages.
Yi et al., “A New Motion Histogram to Index Motion Content in Video Segments,” Pattern Recognition Letters 26(9), Dec. 15, 2004, pp. 1221-1231.
DeMenthon et al., “Video Retrieval Using Spatio-Temporal Descriptors,” in Proceedings of ACM Multimedia, Nov. 2-8, 2003, 10 pages.
Elgammal et al., “Non-Parametric Model for Background Subtraction,” in Proceedings IEEE ICCV, Sep. 1999, 17 pages.
Harris et al., “A Combined Corner and Edge Detector,” in Fourth Alvey Vision Conference, 1988, pp. 147-152.
Mikolajczyk et al., “An Affine Invariant Interest Point Detector,” in European Conference on Computer Vision, 2002, 15 pages.
Mikolajczyk et al., “A Performance Evaluation of Local Descriptors,” in IEEE CVPR, Feb. 23, 2005, 34 pages.
Deng et al., “Unsupervised Segmentation of Color-Texture Regions in Images and Video,” IEEE Transactions on Pattern Analysis and Machine Intelligence 12, May 10, 2001, pp. 1-27.
Bouguet et al., “Requirements for Benchmarking Personal Image Retrieval Systems,” Intel Corporation, Jan. 7, 2006, 12 pages.
Wu et al., “Sampling Strategies for Active Learning in Personal Photo Retrieval,” Content Understanding III, ICME, Toronto, Canada, Jul. 2006, 4 pages.
Jing et al., “A Unified Framework for Image Retrieval Using Keyword and Visual Features,” Proceedings IEEE Transactions on Image Processing, Jul. 7, 2005, p. 979-989.
Rui et al., “Image Retrieval: Current Techniques, Promising Directions, and Open Issues,” Journal of Visual Communication and Image Representation 10, pp. 39-62, 1999.
Zhou et al., “Image Retrieval: Feature Primitives, Feature Representation, and Relevance Feedback,” IEEE Workshop on Content-based Access of Image and Video Libraries, 2000, 6 pages.
Chang et al., “Support Vector Machine Active Learning for Image Retrieval,” Proceedings of the ninth ACM international conference on Multimedia, 2001, 24 pages.
Zhou et al., “Relevance Feedback in Image Retrieval: A Comprehensive Review,” Multimedia Systems, 2003, 25 pages.
Rui et al., “Relevance Feedback: A Power Tool for Interactive Content-Based Image Retrieval,” IEEE Transactions on Circuits and Systems for Video Technology, 1998, 13 pages.
Crucianu et al., “Relevance Feedback for Image Retrieval: a Short Survey,” Report of the DELOS2 European Network of Excellence, Oct. 10, 2004, 21 pages.
Chang et al., “Support Vector Machine Concept-Dependent Active Learning for Image Retrieval,” IEEE Transactions on Multimedia, 2005, 35 pages.
Lim et al., “Home Photo Content Modeling for Personalized Event-Based Retrieval,” IEEE Multimedia, 2003, 10 pages.
Vinay et al., “Comparing Relevance Feedback Algorithms for Web Search,” Proceedings of the World Wide Web Conference, 2005, 2 pages.
Wang et al., “SIMPLIcity: Semantics-Sensitive Integrated Marching for Picture Libraries,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Sep. 2001, 17 pages.
Carson et al., “Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying,” IEEE Transactions on Pettern Analysis and Machine Intelligence, pp. 1026-1038, Aug. 2002.
Sivic et al., “Efficient Object Retrieval From Videos,” Proceedings of the 12th European Signal Processing Conference, Vienna, Austria, 2004, 4 pages.
Wu et al., “Optimal Multimodal Fusion for Multimedia Data Analysis,” Proceedings of the ACM International Conference on Multimedia, 2004, 8 pages.
Chang, et al., “Image Information Systems: Where Do We Go From Here?” IEEE Tra
Kozintsev Igor
Polito Marzia
Yi Haoran
Hanley, Flight and Zimmerman, LLC
Intel Corporation
Koziol Stephen
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