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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hyung-Soo Lee Daijin Kim |
| Copyright Year | 1994 |
| Abstract | The active appearance model (AAM) is a well-known model that can represent a nonrigid object effectively. However, the fitting result is often unsatisfactory when the input image has pose, expression, and illumination variations. To overcome this problem, we propose a tensor-based AAM which consists of two kinds of tensors: image tensor and model tensor. The image tensor is used to estimate the image variation such as the pose, the expression, and the illumination by finding the basis subtensor with minimal reconstruction error. The model tensor is used to generate the specific AAM basis vectors by indexing the model tensor in terms of the estimated image variations. Experimental results show that the proposed tensor-based AAM reduces the fitting error of the conventional AAM by about four pixels. |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 565 |
| Ending Page | 568 |
| Page Count | 4 |
| File Size | 750335 |
| File Format | |
| ISSN | 10709908 |
| Volume Number | 15 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Active appearance model Tensile stress Lighting Face detection Image reconstruction Indexing Face recognition Knowledge engineering Biometrics Intelligent robots tensor-based AAM Active appearance model (AAM) multilinear analysis tensor |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Signal Processing Electrical and Electronic Engineering |
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