摘要
A novel method is proposed in this paper to model changes of object appearance for object contour tracking. Principal component analysis is utilized to learn eigenvectors from a set of the object appearance in our work, and then the current object appearance can be reconstructed by a linear combination of the eigenvectors. To extract the object contour, we perform covariance matching under the variational level set framework. The proposed method is tested on several sequences under large variations, and demonstrates that it outperforms current methods without updating the appearance template.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings |
| 页 | 493-500 |
| 页数 | 8 |
| 版本 | PART 3 |
| DOI | |
| 出版状态 | 已出版 - 2013 |
| 活动 | 20th International Conference on Neural Information Processing, ICONIP 2013 - Daegu, 韩国 期限: 3 11月 2013 → 7 11月 2013 |
出版系列
| 姓名 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| 编号 | PART 3 |
| 卷 | 8228 LNCS |
| ISSN（印刷版） | 0302-9743 |
| ISSN（电子版） | 1611-3349 |
会议
| 会议 | 20th International Conference on Neural Information Processing, ICONIP 2013 |
|---|---|
| 国家/地区 | 韩国 |
| 市 | Daegu |
| 时期 | 3/11/13 → 7/11/13 |
指纹
探究 'PCA-Based appearance template learning for contour tracking' 的科研主题。它们共同构成独一无二的指纹。引用此
Ma, B., Hu, H., Li, P., & Han, Y. (2013). PCA-Based appearance template learning for contour tracking. 在 Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings (PART 3 编辑, 页码 493-500). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 8228 LNCS, 号码 PART 3). https://doi.org/10.1007/978-3-642-42051-1_61