Name
Abstract | ||
|---|---|---|
Active Appearance Model is a well-known model that can represent a non-rigid object effectively. However, since it uses the fixed appearance model, the fitting results are often unsatisfactory when the imaging condition of the target image is different from that of training images. To alleviate this problem, incremental AAM was proposed which updates its appearance bases in an on-line manner. However, it can not deal with the sudden changes of illumination. To overcome this, we propose a novel scheme to update the appearance bases. When a new person appears in the input image, we synthesize illuminated images of that person and update the appearance bases of AAM using it. Since we update the appearance bases using synthesized illuminated images in advance, the AAM can fit their model to a target image well when the illumination changes drastically. The experimental results show that our proposed algorithm improves the fitting performance over both the incremental AAM and the original AAM. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-77255-2_83 | PCM |
Keywords | Field | DocType |
target image,appearance base,incremental aam,synthesized illuminated image,fixed appearance model,input image,illuminated image,training image,well-known model,synthesized illumination image,original aam,active appearance model | Computer vision,Pattern recognition,Computer science,Active appearance model,Artificial intelligence | Conference |
Volume | ISSN | ISBN |
4810 | 0302-9743 | 3-540-77254-5 |
Citations | PageRank | References |
1 | 0.36 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyung-Soo Lee | 1 | 132 | 13.10 |
| Jaewon Sung | 2 | 152 | 9.57 |
| Daijin Kim | 3 | 1882 | 126.85 |