Image analysis – Learning systems – Trainable classifiers or pattern recognizers
Reexamination Certificate
2005-10-25
2005-10-25
Dastouri, Mehrdad (Department: 2623)
Image analysis
Learning systems
Trainable classifiers or pattern recognizers
C382S117000, C340S005530, C706S020000
Reexamination Certificate
active
06959109
ABSTRACT:
A system and method are disclosed for determining the pose angle of an object in an input image. In a preferred embodiment, the present system comprises a pose estimator having a prototype projector, a regression estimator, and an angle calculator. The prototype projector is preferably adapted to reduce the input image dimensionality for faster further processing by projecting the input pixels of the image onto a Self-Organizing Map (SOM) neural network. The regression estimator is preferably implemented as a neural network and adapted to map the projections to a pattern unique to each pose. The angle calculator preferably includes a curve fitter and an error analyzer. The curve fitter is preferably adapted to estimate the pose angle from the mapping pattern. The error analyzer is preferably adapted to produce a confidence signal representing the likelihood of the input image being a face at the calculated pose. The system also preferably includes two network trainers responsible for synthesizing the neural networks.
REFERENCES:
patent: 5239594 (1993-08-01), Yoda
patent: 5642431 (1997-06-01), Poggio et al.
patent: 5850470 (1998-12-01), Kung et al.
patent: 6128397 (2000-10-01), Baluja et al.
patent: 6144755 (2000-11-01), Niyogi et al.
patent: 6429699 (2002-08-01), Shi et al.
Kohonen et al., “Engineering Applications of the Self-Organizing Map,” IEEE 1996, pp. 1358-1384.
Amari, “Training Error, Generalization Error and Learning Curves in Neural Learning,” IEEE 1995, pp. 4-5.
Rowley et al., “Rotation Invariant Neural Network-Based Face Detection,” IEEE 1998, pp. 1-7.
Lawrence et al., “Convolution Neural Networks for Face Recognition,” IEEE 1996, pp. 217-222.
Rowley et al., “Rotation Invariant Neural Network-Based Face Detection,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1-7 (Jun. 1998).
Li et al., “Support Vector Regression and Classification Based Multi-view Face Detection and Recognition,”Proceedings IEEE International Conference on Automatic Face and Gesture Recognition, Mar. 2000.
Yan et al., “Ensemble SVM Regression Based Multi-View Face Detection System,” Microsoft Research Technical Report MSR-TR-2001-09, Jan. 18, 2001.
Shimizu et al., “Head Pose Determination from One Image Using a Generic Model,”Proceedings IEEE International Conference on Automatic Face and Gesture Recognition, Apr. 1998.
Kohonen, “Self-Organizing Maps,” ISBN 3-540-62017-6, Springer-Verlag 2nded., 1997 (Title page, table of contents and index only).
Beyer Weaver & Thomas LLP
Dastouri Mehrdad
Identix Incorporated
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