Carnegie Mellon University
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Spatio-Temporal Facial Expression Segmentation
Head: Fernando De la Torre Frade
Contact: Fernando De la Torre Frade
Mailing address:
Carnegie Mellon University
Robotics Institute
211 Smith Hall
Pittsburgh, PA 15213
Associated center(s) / consortia:
 Vision and Autonomous Systems Center (VASC)
Associated lab(s) / group(s):
 People Image Analysis Consortium
 Face Group
Temporal segmentation of facial gestures from video sequences is an important unsolved problem for automatic facial image analysis. At least two problems contribute to the challenge of temporal segmentation. These are the difficulty to register the rigid and non-rigid motion of the face, and the large variability in temporal scale of facial gestures. To address these challenges, we propose a two-step approach to temporally segment facial gestures. The first step clusters shape and appearance features invariantly to geometric transformations using Parameterized Cluster Analysis (PaCA). PaCA is a novel method that jointly performs registration and clustering. The second step temporally groups the resulting clusters into temporally coherent facial gestures.