Learning a face model for tracking and recognition
作者： Zakaria Ajmal , Jean- Yves Bouguet , Russell M. Mersereau
DOI: 10.1109/ICASSP.2002.5745437
关键词:
摘要: This paper describes a system for learning face model that is used 3D tracking of the human face. The modeled as linear combination shape basis vectors and action vectors. Shape space models difference in different people while facial expressions. First, real stereo data to learn these using Principal Component Analysis. Then this low-complexity simultaneously track shape, pose expression from monocular image sequence. main contribution deformation data. Results model-based subjects not included training set show derived robust generalizes well.
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