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Capturing Complex Facial Muscle Relations for Expression Recognition

Explore Interval Temporal Bayesian Network (ITBN) capturing spatio-temporal facial muscle events for effective recognition of expressions. The model interprets facial expressions as sequential or overlapping muscle contractions, providing enhanced performance over existing dynamic models like HMM.

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Capturing Complex Facial Muscle Relations for Expression Recognition

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  1. Session 3D: Thursday Afternoon, June 27th Capturing Complex Spatio-Temporal Relations among Facial Muscles for Facial Expression Recognition Ziheng Wang, Shangfei Wang, Qiang Ji

  2. P3D-06 Capturing Complex Spatio-Temporal Relations among Facial Muscles for Facial Expression Recognition • Introduction • Model the facial expression as a complex activity consisting of sequential or overlapping facial muscle events • Propose an Interval Temporal Bayesian Network (ITBN) to capture spatio-temporal relations among the primitive facial events for expression recognition Interval Temporal Bayesian Network B before meet E1 A IAB overlap start IBC C B E2 IAC C during B C E3 finish equal B C E4 B C • ExperimentalResults • ITBN outperforms other time-slice based dynamic models such as HMM • ITBN achieves comparable and even better performance than the related works B t C Contributions C B B C

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