Detecting Facial Expressions for Monitoring Patterns of Emotional Behavior
International Journal of Monitoring and Surveillance Technologies Research
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A new technique for segmenting and tracking human faces in video sequences is presented. The technique relies on morphological tools such as connected operators to extract the connected component that more likely belongs to a face and partition projection to track this component through the sequence. A Binary Partition Tree (BPT) is used to implement the connected operator. The BPT is constructed based on chrominance criteria and its nodes are analyzed so that the selected node maximizes an estimation of the likelihood of being part of a face. The tracking is performed using a partition projection approach. Images are divided into face and non-face parts, which are tracked through the sequence. The technique has been successfully assessed using several test sequences from the MPEG-4 (raw format) and the MPEG-7 databases (MPEG-1 format).