An ASM fitting method based on machine learning that provides a robust parameter initialization for AAM fitting

Matthias Wimmer, Shinya Fujie, Freek Stulp, Tetsunori Kobayashi, Bernd Radig

研究成果: Conference contribution

2 引用 (Scopus)

抜粋

Due to their use of information contained in texture, Active Appearance Models (AAM) generally outperform Active Shape Models (ASM) in terms of fitting accuracy. Although many extensions and improvements over the original AAM have been proposed, on of the main drawbacks of AAMs remains its dependence on good initial model parameters to achieve accurate fitting results. In this paper, we determine the initial model parameters for AAM fitting with ASM fitting, and use machine learning techniques to improve the scope and accuracy of ASM fitting. Combining the precision of AAM fitting with the large radius of convergence of learned ASM fitting improves the results by an order of magnitude, as our empirical evaluation n a database of publicly available benchmark images demonstrates.

元の言語English
ホスト出版物のタイトル2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008
DOI
出版物ステータスPublished - 2008 12 1
イベント2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008 - Amsterdam, Netherlands
継続期間: 2008 9 172008 9 19

出版物シリーズ

名前2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008

Conference

Conference2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008
Netherlands
Amsterdam
期間08/9/1708/9/19

    フィンガープリント

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

これを引用

Wimmer, M., Fujie, S., Stulp, F., Kobayashi, T., & Radig, B. (2008). An ASM fitting method based on machine learning that provides a robust parameter initialization for AAM fitting. : 2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008 [4813465] (2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008). https://doi.org/10.1109/AFGR.2008.4813465