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Global Semantic Relationships for Facial Action Unit Recognition

Explore how global semantic relations among facial action units are captured using Restricted Boltzmann Machines for improved AU recognition. Current methods model pair-wise AU relations, but the proposed approach enhances the understanding of happiness, anger, fear, surprise, and more. This session delves into top-down and bottom-up approaches for AU recognition from image measurements, offering insights into the complexities of facial expressions.

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Global Semantic Relationships for Facial Action Unit Recognition

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  1. Poster Spotlights Session 4B: Friday Afternoon, December 6th Capturing Global Semantic Relationships for Facial Action Unit Recognition Ziheng Wang, Yongqiang Li, Shangfei Wang, Qiang Ji

  2. Capturing Global Semantic Relationships for Facial Action Unit Recognition P4B-09 • Motivation • Facial action units (AU) are NOT independent • Current methods can only model pair-wise AU relations • Propose to use RBM to capture global AU relations for AU recognition Happiness Anger Fear Surprise Approach Result CK+ Top Down: Global semantic relations among facial action units Raise eye lid Raise eye lid Raise eye lid Raise eye lid Stretch mouth Stretch mouth Stretch mouth Stretch mouth Raise cheek Raise cheek Raise cheek Raise cheek Pull lip corner Pull lip corner Pull lip corner Pull lip corner Raise brow Raise brow Raise brow Raise brow Bottom Up: AU recognition from image measurements SEMAINE

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