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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Li Zhang Haizhou Ai |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing (Li Zhang; Haizhou Ai) |
| Abstract | Active shape model is an efficient way for localizing objects with variable shapes. When ASM is extended to multi-view cases, the parameter estimation approaches in previous works are often sensitive to the initial view, as they do not handle the unreliability of local texture search, which can be caused by bad initialization or cluttered background. To overcome this problem, we propose a novel algorithm for parameter estimation, using robust estimators to remove outliers. By weighting dynamically, our method acts as a model selection method, which reveals the hidden shape and view parameters from noisy observations of local texture models. Experiments and comparisons on multi-view face alignment are carried out to show the efficiency of our approach |
| Sponsorship | IEEE CPS |
| Starting Page | 469 |
| Ending Page | 468 |
| File Size | 327029 |
| Page Count | 0 |
| File Format | |
| ISBN | 0769525210 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2006.834 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-08-20 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Active shape model Robustness Parameter estimation Training data Principal component analysis Solid modeling Computer science Multi-stage noise shaping Statistical distributions Humans |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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