NDLI: Automatic facial action units recognition. Retrieved from http://www.ecse.rpi.edu/~cvrl/tongy/aurecognition.html (2007)

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Automatic facial action units recognition. Retrieved from http://www.ecse.rpi.edu/~cvrl/tongy/aurecognition.html (2007)

Content Provider	CiteSeerX
Author	Ji, Q. Tong, Y. Liao, Wenhui Liao, W. Ji, Qiang Tong, Yan
Abstract	Abstract A system that could automatically analyze the facial actions in real-time has applications in a wide range of different fields. The previous facial action unit (AU) recognition approaches often recognize AUs or certain AU combinations in-dividually and statically, ignoring the semantic relationships among AUs and the dynamics of AUs. Hence, these approaches cannot always recognize AUs reliably, robustly, and consistently due to the richness, ambiguity, and the dynamic nature of facial actions. In this work, a novel AU recognition system is proposed to sys-tematically account for the relationships among AUs and their temporal evolutions based on a dynamic Bayesian network (DBN). The DBN provides a coherent and unified hierarchical probabilistic framework to represent probabilistic relationships among various AUs and to account for the temporal changes in facial action devel-opment. Within the proposed system, robust computer vision techniques are used to obtain AU measurements. And such AU measurements are then applied as evidence to the DBN for inferring various AUs. The experiments show that the integration of AU relationships and AU dynamics with AU measurements yields significant improvement of AU recognition, especially under realistic environments including illumination variation, face pose variation, and occlusion.
File Format	PDF
Publisher Date	2007-01-01
Access Restriction	Open
Subject Keyword	Recognition Approach Facial Action Devel-opment Au Dynamic Au Recognition Au Relationship Robust Computer Vision Technique Face Pose Variation Realistic Environment Certain Au Combination Illumination Variation Probabilistic Relationship Au Measurement Novel Au Recognition System Various Au Facial Action Previous Facial Action Unit Automatic Facial Action Unit Recognition Cvrl Tongy Aurecognition Unified Hierarchical Probabilistic Framework Au Measurement Yield Significant Improvement
Content Type	Text

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