2012年
Orientation selectivity for representing dynamic diversity of facial expressions
Journal of Computers
- ,
- 巻
- 7
- 号
- 9
- 開始ページ
- 2107
- 終了ページ
- 2113
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.4304/jcp.7.9.2107-2113
This paper presents a representation method of facial expression changes using Adaptive Resonance Theory (ART) networks. Our method extracts orientation selectivity of Gabor wavelets on ART networks, which are unsupervised and self-organizing neural networks that contain a stabilityplasticity tradeoff. The classification ability of ART is controlled by a parameter called the attentional vigilance parameter. However, the networks often produce redundant categories. The proposed method produces suitable vigilance parameters according to classification granularity using orientation selectivity. Moreover, the method can represent the appearance and disappearance of facial expression changes to detect dynamic, local, and topological feature changes from obtained whole facial images. © 2012 ACADEMY PUBLISHER.
- リンク情報
- ID情報
-
- DOI : 10.4304/jcp.7.9.2107-2113
- ISSN : 1796-203X
- SCOPUS ID : 84867004577