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Carnegie Mellon Robotics Institute

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Abstract

Previous research in automatic facial expression recognition has been limited to recognition of gross expression categories (e.g., joy or anger) in posed facial behavior under well-controlled conditions (e.g., frontal pose and minimal out-of-plane head motion). We have developed a system that detects a discrete and important facial action (e.g., eye blinking) in spontaneously occurring facial behavior that has been measured with non-frontal pose, moderate out-of-plane head motion, and occlusion. The system recovers 3D motion parameters, stabilizes facial regions, extracts motion and appearance information, and recognizes discrete facial actions in spontaneous facial behavior. We tested the system in video data from a 2-person interview. The 10 subjects were ethnically diverse, action units occurred during speech, and out-of-plane motion and occlusion from head motion and glasses were common. The video data were originally collected to answer substantive questions in psychology, and represent a substantial challenge to automated AU recognition. In analysis of blinks, the system achieved 98% accuracy.

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

Number of pages: 24

Text Reference

Jeffrey Cohn, Jing Xiao, Tsuyoshi Moriyama, Zara Ambadar, and Takeo Kanade, "Automatic recognition of eye blinking in spontaneously occurring behavior," Behavior Research Methods, Instruments, and Computers, Vol. 35, 2003, pp. 420 - 428.

BibTeX Reference

@article{Cohn_2003_4809,
   author = "Jeffrey Cohn and Jing Xiao and Tsuyoshi Moriyama and Zara Ambadar and Takeo Kanade",
   title = "Automatic recognition of eye blinking in spontaneously occurring behavior",
   journal = "Behavior Research Methods, Instruments, and Computers",
   pages = "420 - 428",
   year = "2003",
   volume = "35",
}

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