We propose a fitting method using a model that integrates face and body shape variance information for upper-body contour extraction. Accurate body-contour extraction is necessary for various applications, such as pose estimation, gesture recognition, and so on. In this study, we regard it as the shape model fitting problem. A model including shape variance information can fit to the contour robustly even in the noisy case. AAMs are one of these models and can fit to a face successfully. It needs appearance information for effective fitting, but it can not be used in our case because appearance of upper-body easily changes by clothes. Instead of intensity image, proposed method uses edge image as appearance information. However, discrimination between a true contour edge of upper-body and other edges is difficult. To solve this problem, we integrate shapes of upper-body and face. It is expected that this integrated model is more robust to edges in clutter background and various locations of the body than a body shape model using only body shape information. We conduct experiments and confirm improvement in accuracy by integration of face and body variance information.
|ジャーナル||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|出版ステータス||Published - 2009|
|イベント||3rd Pacific Rim Symposium on Image and Video Technology, PSIVT 2009 - Tokyo, Japan|
継続期間: 2009 1 13 → 2009 1 16
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)