A Dynamic Texture-Based Approach to Recognition of Facial Actions and Their Temporal Models

—In this work we propose a dynamic-texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modelling the dynamics and the appearance in the face region of an input video are compared: an extended version of Motion History Images and a novel method based on Non-rigid Registration using Free-Form Deformations (FFDs). The extracted motion representation is used to derive motion orientation histogram descriptors in both the spatial and temporal domain. Per AU, a combination of discriminative, frame-based GentleBoost ensemble learners and dynamic, generative Hidden Markov Models detects the presence of the AU in question and its temporal segments in an input image sequence. When tested for recognition of all 27 lower and upper face AUs, occurring alone or in combination in 264 sequences from the MMI fa...

• Type: Journal
• Year: 2010
• Where: PAMI
• Authors: Sander Koelstra, Maja Pantic, Ioannis Patras
• Keywords: Atomic Facial Gestures, FFD Method, PAMI 2010, Temporal Segments