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Carnegie Mellon Robotics Institute

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Abstract

Most automatic expression analysis systems attempt to recognize a small set of prototypic expressions (e.g., happiness and anger). Such prototypic expressions, however, occur infrequently. Human emotions and intentions are communicated more often by changes in one or two discrete facial features. We develop an automatic system to analyze subtle changes in facial expressions based on both permanent (e.g., mouth, eye, and brow) and transient (e.g., furrows and wrinkles) facial features in a nearly frontal image sequence. Multi-state facial component models are proposed for tracking and modeling different facial features. Based on these multi-state models, and without artificial enhancement, we detect and track the facial features, including mouth, eyes, brow, cheeks, and their related wrinkles and facial furrows. Moreover we recover detailed parametric descriptions of the facial features. With these features as the inputs, 11 individual action units or action unit combinations are recognized by a neural network algorithm. A recognition rate of 96.7% is obtained. The recognition results indicate that our system can identify action units regardless of whether they occur singly or in combinations.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): Face Group and Component Analysis

Associated Project(s): Facial Expression Analysis and Face Databases

Text Reference

Ying-Li Tian, Takeo Kanade, and Jeffrey Cohn, "Recognizing Lower Face Action Units for Facial Expression Analysis," Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), March, 2000, pp. 484 - 490.

BibTeX Reference

@inproceedings{Tian_2000_3252,
   author = "Ying-Li Tian and Takeo Kanade and Jeffrey Cohn",
   title = "Recognizing Lower Face Action Units for Facial Expression Analysis",
   booktitle = "Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG'00)",
   pages = "484 - 490",
   month = "March",
   year = "2000",
}

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