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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2621
Title: Locally linear models on face appearance manifolds with application to dual-subspace based classification
Authors: Fan, Wei
Yeung, Dit-Yan
Keywords: Face recognition
Clustering
Distance measure
Classification
Images
Issue Date: Jun-2006
Citation: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), New York, U.S.A., 17-22 June 2006, vol. 2, p. 1384-1390
Abstract: Recently, there has been a flurry of research on face recognition based on multiple images or shots from either a video sequence or an image set. This paper is also such an attempt in multiple-shot face recognition. Specifically, we propose a novel nonparametric method that first extracts discriminating local models via clustering. We apply a hierarchical distance-based clustering procedure according to some distance measure on the appearance manifold to cluster similar face images together. Based on the local models extracted, we then construct the intrapersonal and extrapersonal subspaces. Given a new test image, the angle between the projections of the image onto the two subspaces is used as a distance measure for classification. Since a test example contains multiple face images in multiple-shot face recognition, the final classification combines the classification decisions of all individual test images via a majority voting scheme. We compare our method empirically with some previous methods based on a database of video sequences of human faces, showing that out method significantly outperforms other methods.
Rights: © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
URI: http://hdl.handle.net/1783.1/2621
Appears in Collections:CSE Conference Papers

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