Image analysis – Pattern recognition – Classification
Reexamination Certificate
2007-07-17
2007-07-17
Mariam, Daniel (Department: 2624)
Image analysis
Pattern recognition
Classification
C706S020000
Reexamination Certificate
active
10645084
ABSTRACT:
There is provided a method for classifying, identifying or verifying an object by representing the object by a respective sequence of vectors, modeling the sequence of vectors with a respective generative model such that the object is represented by the generative model, computing the distances between the generative models to form one or many kernel matrices based on the distance metric, and using the kernel matrices to classify, identify or verify the object. There is provided a system for determining a classification of an object having a representation module for representing an object by a respective sequence of vectors, a modeling module for modeling the sequence of vectors with a respective generative model such that the object is represented by the generative model, a distance computing module for calculating the distances between the generative models to form one or many kernel matrices based on the distance metric, and a determination module for classifying, identifying or verifying the object based on the kernel matrices.
REFERENCES:
patent: 6061652 (2000-05-01), Tsuboka et al.
patent: 2003/0041041 (2003-02-01), Cristianini
patent: 2005/0100992 (2005-05-01), Noble
Moreno, et al. “Using the Fisher Kernel Method for Web Audio Classification”, IEEE, pp. 2417-2420, 2000.
Hollmén, et al “A Learning Vector Quantization Algorithm for Probabilistic Models” European Signal Processing Conference, vol. II, pp. 721-724, 2000.
Bengio, et al “Learning the Decision Function for Speaker Verification”, IEEE, pp. 425-428, 2001.
Gu, Y. and T. Thomas, “A Text-Independent Speaker Verification System Using Support Vector Machines Classifier,” Eurospeech 2001 (3 pp.).
Fine, S. et al., “Enhancing GMM Scores Using SVM ‘Hints’”, Eurospeech 2001 (4 pp.).
Kharroubi, J. et al., “Combining GMM's with Support Vector Machines for Text-Independent Speaker Verification,” Eurospeech 2001, (4 pp.).
Lodhi, H. et al., “Text Classification Using String Kernels,” Journal of Machine Learning Research 2 (2002) pp. 419-444.
Jaakkola, T. et al., “Using the Fisher kernel method to detect remote protein homologies,” in Proceedings of the International Conference on Intelligent Systems for Molecular Biology, Aug. 1999 (5 pp.).
Jaakkola, T.S. and D. Haussler, “Exploting generative models in discriminative classifiers,” in Advances in Neural Information Processing Systems, vol. 11 (1999) 11 pp.
Fine, S. et al., “A Hybrid GMM/SVM Approach to Speaker Identification,” In Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2001 (4 pp.).
Smith, N. et al., Data-Dependent Kernels in SVM Classification of Speech Patterns, Cambridge University Engineering Department Technical Report 387 (Apr. 2001) 56 pp.).
Ho Purdy
Moreno Pedro J.
Hewlett--Packard Development Company, L.P.
Lange Richard P.
LandOfFree
Method and apparatus for object identification,... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method and apparatus for object identification,..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method and apparatus for object identification,... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3757111