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We propose a new approach for constructing mid-level visual features for image classification. We represent an image using the outputs of a collection of binary classifiers. These binary classifiers are trained to differentiate pairs of object classes in an object hierarchy. Our feature representation implicitly captures the hierarchical structure in object classes. We show that our proposed approach...
Non-rigid object alignment is especially challenging when only a single appearance template is available and target and template images fail to match. Two sources of discrepancy between target and template are changes in illumination and non-rigid motion. Because most existing methods rely on a holistic representation for the alignment process, they require multiple training images to capture appearance...
This paper presents a multi-state hierarchical approach for facial feature tracking. A hierarchical formulation of statistical shape models is proposed to characterize both global shape constraints of human faces and local structural details of facial components. Gabor wavelets and gray level profiles are integrated for effective and efficient representation of feature points. Furthermore, multi-state...
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