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FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
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The Journal of Machine Learning Research
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ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Application of the Karhunen-Loève Expansion to Feature Selection and Ordering
IEEE Transactions on Computers
Principal Angles Separate Subject Illumination Spaces in YDB and CMU-PIE
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boosting constrained mutual subspace method for robust image-set based object recognition
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
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ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
A framework for 3d object recognition using the kernel constrained mutual subspace method
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Learning discriminative canonical correlations for object recognition with image sets
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
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In this paper, we propose the Compound Mutual Subspace Method (CPMSM) as a theoretical extension of the Mutual Subspace Method, which can efficiently handle multiple sets of patterns by representing them as subspaces. The proposed method is based on the observation that there are two types of subspace perturbations. One type is due to variations within a class and is therefore defined as "within-class subspace". The other type, named "between-class subspace", is characterized by differences between two classes. Our key idea for CPMSM is to suppress within-class subspace perturbations while emphasizing between-class subspace perturbations in measuring the similarity between two subspaces. The validity of CPMSM is demonstrated through an evaluation experiment using face images from the public database VidTIMIT.