Face recognition is one of the most challenging computer vision research topics since faces appear differently even for the same person due to expression, pose, lighting, occlusion and many other confounding factors in real life. During the past thirty years, a number of face recognition techniques have been proposed. However, all of these methods focus exclusively on image-based face recognition that uses a still image as input data. One problem with the image-based face recognition is that it is possible to use a pre-recorded face photo to confuse a camera to take it as a live subject. The second problem is that the image-based recognition accuracy is still too low in some practical applications comparing to other high accuracy biometric technologies. To alleviate these problems, video based face recognition has been proposed recently. One of the major advantages of video-based face recognition is to prevent the fraudulent system penetration by pre-recorded facial images. The great difficulty to forge a video sequence (possible but very difficult) in front of a live video camera may ensure that the biometric data come from the user at the time of authentication. Another key advantage of the video based method is that more information is available in a video sequence than in a single image. If the additional information can be properly extracted, we can further increase the recognition accuracy. / In this thesis, we develop a new video-to-video face recognition algorithm [86]. The major advantage of the video based method is that more information is available in a video sequence than in a single image. In order to take advantage of the large amount of information in the video sequence and at the same time overcome the processing speed and data size problems we develop several new techniques including temporal and spatial frame synchronization, multi-level subspace analysis, and multi-classifier integration for video sequence processing. An aligned video sequence for each person is first obtained by applying temporal and spatial synchronization, which effectively establishes the face correspondence using the information of both audio and video, then multi-level subspace analysis or multi-classifier integration is employed for further analysis based on the synchronized sequence. The method preserves all the temporal-spatial information contained in a video sequence. Near perfect classification results are obtained on the largest available XM2VTS face video database. In addition, using a similar framework, two kinds of much improved still image based face recognition algorithms [93][94] are developed by incorporating the Gabor representation, nonparametric feature extraction method, and multiple classifier integration techniques. Extensive experiments on two famous face databases (XM2VTS database and Purdue database) clearly show the superiority of our new algorithms. / by Li Zhifeng. / "March 2006." / Adviser: Xiaoou Tang. / Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6621. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 105-114). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_343790 |
| Date | January 2006 |
| Contributors | Li, Zhifeng., Chinese University of Hong Kong Graduate School. Division of Information Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, theses |
| Format | electronic resource, microform, microfiche, 1 online resource (114 p. : ill.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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