ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Analysis of head and facial gestures using facial landmark trajectories
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
Spatiotemporal-boosted DCT features for head and face gesture analysis
HBU'10 Proceedings of the First international conference on Human behavior understanding
Robust classification of face and head gestures in video
Image and Vision Computing
A real-time framework for eye detection and tracking
Journal of Real-Time Image Processing
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Tracking facial features across large head rotations is a challenging research problem. Both 2D and 3D model based approaches have been proposed for feature analysis from multiple views. Accurate feature tracking enables useful video processing applications like emblem detection(an event or movement that symbolizes an idea), facial expressions recognition, morphing and synthesis. A crucial requirement is generalizability of the tracking framework across appearance variations, presence of facial hair and illumination changes. We propose a framework to detect emblems that combines active shape model with a predictive face aspect model to track features across large head movements and runs close to real time. Active Shape Model(ASM) is a deformable model for shape registration that detect facial features by combining prior shape information with the observed image data. Our view based framework represents various head poses by multiple 2D shape models and accounts for large head rotations by dynamically switching between them. Our switching variable (the current model to use) is discriminatively predicted from the SIFT descriptors computed over the bounding box of low resolution face image. We demonstrate the use of tracking framework to recognize high level events like head nodding, shaking and eye blinking.