Active shape models—their training and application
Computer Vision and Image Understanding
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Optical Flow Constraints on Deformable Models with Applications to Face Tracking
International Journal of Computer Vision
International Journal of Computer Vision
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Statistical Cue Integration in DAG Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
Blob Analysis of the Head and Hands: A Method for Deception Detection
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 1 - Volume 01
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
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We present a dynamic data-driven framework for tracking gestures and facial expressions from monocular sequences. Our system uses two cameras, one for the face and one for the body view for processing in different scales. Specifically, and for the gesture tracking module, we track the hands and the head, obtaining as output the blobs (ellipses) of the ROIs, and we detect the shoulder positions with straight lines. For the facial expressions, we first extract the 2D facial features, using a fusion between KLT tracker and a modified Active Shape Model, and then we obtain the 3D face mask with fitting a generic model to the extracted 2D features. The main advantages of our system are (i) the adaptivity, i.e., it is robust to external conditions, e.g., lighting, and independent from the examined individual, and (ii) its computational efficiency, providing us results off- and online with a rates higher than 20fps.