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 CHIL and VACE test data sets. Finally, we offer some analysis on both speed and accuracy performance
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References
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Nechyba, M.C., Brandy, L., Schneiderman, H. (2008). PittPatt Face Detection and Tracking for the CLEAR 2007 Evaluation. In: Stiefelhagen, R., Bowers, R., Fiscus, J. (eds) Multimodal Technologies for Perception of Humans. RT CLEAR 2007 2007. Lecture Notes in Computer Science, vol 4625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68585-2_10
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DOI: https://doi.org/10.1007/978-3-540-68585-2_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68584-5
Online ISBN: 978-3-540-68585-2
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