Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/55121
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Type: Conference paper
Title: Face Recognition from Video by Matching Image Sets
Author: Chin, T.J.
U, J.
Schindler, K.
Suter, D.
Citation: Proceedings of Digital Image Computing: Techniques and Applications, held in Cairns, Queensland, Australia, 2005: www1-7
Publisher: IEEE
Publisher Place: Online
Issue Date: 2005
ISBN: 0769524672
Conference Name: Digital Image Computing: Techniques and Applications (2005 : Cairns, Australia)
Statement of
Responsibility: 
Tat-Jun Chin, James U, Konrad Schindler and David Suter
Abstract: As opposed to still-image based paradigms, video-based face recognition involves identifying a person from a video input. In video-based approaches, face detection and tracking are performed together with recognition, as usually the background is included in the video and the person could be moving or being captured unknowingly. By detecting and raster-scanning a face sub-image to be a vector, we can concatenate all extracted vectors to form an image set, thus allowing the application of face recognition algorithms based on matching image sets. It has been reported that linear subspace-based methods for face recognition using image sets achieve good recognition results. The challenge that remains is to update the linear subspace representation and perform recognition on-the-fly so that the recognition from-video objective is not defeated. Here, we demonstrate how this can be achieved by using a well-studied incremental SVD updating procedure. We then present our online face recognition-from-video framework and the recognition results obtained.
RMID: 0020093459
DOI: 10.1109/DICTA.2005.36
Appears in Collections:Computer Science publications

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