PittPatt Face Detection and Tracking for the CLEAR 2007 Evaluation

Abstract. This paper describes Pittsburgh Pattern Recognition’s participation in the face detection and tracking tasks for the CLEAR 2007 evaluation. Since CLEAR 2006, we have made substantial progress in optimizing our algorithms for speed, achieving better than real-time processing performance for a speed-up of more than 500× over the past two years. At the same time, we have maintained the high level of accuracy of our algorithm. In this paper, 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 report our results, both in terms of accuracy and speed, over the two test data sets: (1) the CHIL Seminar corpus, and (2) the VACE Multisite Meeting corpus. Finally, we offer some analysis on both speed and accuracy performance, and how these compare with our performance in CLEAR 2006. 1 System Description Similar to our work for the CLEAR 2006 evaluatio...

• Type: Conference
• Year: 2007
• Where: CLEAR
• Authors: Michael C. Nechyba, Louis Brandy, Henry Schneiderman
• Keywords: Biometrics, CLEAR 2007, CLEAR 2007 Evaluation, Face Detection, Frame-based Face Detection