Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Tracking and Segmenting People in Varying Lighting Conditions Using Colour
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
W4: Who? When? Where? What? A Real Time System for Detecting and Tracking People
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Towards Vision-Based 3-D People Tracking in a Smart Room
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Pointing gesture recognition based on 3D-tracking of face, hands and head orientation
Proceedings of the 5th international conference on Multimodal interfaces
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Tracking multiple speakers with probabilistic data association filters
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
Audio-visual multi-person tracking and identification for smart environments
Proceedings of the 15th international conference on Multimedia
Multimodal Technologies for Perception of Humans
Multi-level Particle Filter Fusion of Features and Cues for Audio-Visual Person Tracking
Multimodal Technologies for Perception of Humans
Multispeaker Localization and Tracking in Intelligent Environments
Multimodal Technologies for Perception of Humans
Multi-person Tracking Strategies Based on Voxel Analysis
Multimodal Technologies for Perception of Humans
The AIT 2D Face Detection and Tracking System for CLEAR 2007
Multimodal Technologies for Perception of Humans
Efficient person identification using active cameras in a smartroom
Proceedings of the 1st ACM international workshop on Multimodal pervasive video analysis
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Simultaneous tracking of multiple persons in real world environments is an active research field and several approaches have been proposed, based on a variety of features and algorithms. In this work, we present 2 multimodal systems for tracking multiple users in a smart room environment. One is a multi-view tracker based on color histogram tracking and special person region detectors. The other is a wide angle overhead view person tracker relying on foreground segmentation and model-based tracking. Both systems are completed by a joint probabilistic data association filter-based source localization framework using input from several microphone arrays. We also very briefly present two intuitive metrics to allow for objective comparison of tracker characteristics, focusing on their precision in estimating object locations, their accuracy in recognizing object configurations and their ability to consistently label objects over time. The trackers are extensively tested and compared, for each modality separately, and for the combined modalities, on the CLEAR 2006 Evaluation Database.