Feature-centric evaluation for efficient cascaded object detection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Learning a restricted Bayesian network for object detection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
The AIT 2D Face Detection and Tracking System for CLEAR 2007
Multimodal Technologies for Perception of Humans
PittPatt Face Detection and Tracking for the CLEAR 2007 Evaluation
Multimodal Technologies for Perception of Humans
Adaptive facial expression recognition using inter-modal top-down context
ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
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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) motionbased 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.