PittPatt Face Detection and Tracking for the CLEAR 2006 Evaluation
This paper describes Pittsburgh Pattern Recognition’s participation in the face detection and tracking tasks for the CLEAR 2006 evaluation. We first give a system overview, briefly explaining the three main stages of processing: (1) frame-based face detection; (2) motion-based tracking; and (3) track filtering. Second, we summarize and analyze our system’s performance on two test data sets: (1) the CHIL Interactive Seminar corpus, and (2) the VACE Multi-site Conference Meeting corpus. We note that our system is identically configured for all experiments, and, as such, makes use of no site-specific or domain-specific information; only video continuity is assumed. Finally, we offer some concluding thoughts on future evaluations.
KeywordsFalse Alarm Ground Truth False Alarm Rate Face Detection Visible Landmark
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