Tensor-Based AAM with Continuous Variation Estimation: Application to Variation-Robust Face Recognition
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SCOPUS
- Title
- Tensor-Based AAM with Continuous Variation Estimation: Application to Variation-Robust Face Recognition
- Authors
- Hyung-Soo Lee; Kim, D
- Date Issued
- 2009-06
- Publisher
- IEEE COMPUTER SOC
- Abstract
- The Active appearance model (AAM) is a well-known model that can represent a nonrigid object effectively. However, because it uses a fixed model of shape and appearance, the fitting result is often unsatisfactory when an input image deviates from the training images. To obtain more robust AAM fitting, we propose a tensor-based AAM that can handle a variety of subjects, poses, expressions, and illuminations in the tensor algebra framework. It consists of an image tensor and a model tensor. The image tensor is used to estimate image variations such as pose, expression, and illumination of the input image. Here, we introduce two different variation estimation approaches: discrete and continuous variation estimation. Then, the model tensor generates a variation-specific AAM from a tensor representation, using the estimation results. This process ensures more accurate fitting results. To validate the usefulness of the tensor-based AAM, we performed variation-robust face recognition using the tensor-based AAM fitting results. To do this, we propose indirect AAM feature transformation. Experimental results show that the tensor-based AAM with continuous variation estimation outperforms that with discrete variation estimation and conventional AAM in terms of the average fitting error and the face recognition rate.
- Keywords
- Tensor algebra; multilinear analysis; AAM; indirect AAM feature transformation; variation-robust face recognition; ACTIVE APPEARANCE MODELS
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/28443
- DOI
- 10.1109/TPAMI.2008.286
- ISSN
- 0162-8828
- Article Type
- Article
- Citation
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 31, no. 6, page. 1102 - 1116, 2009-06
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