Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
International Journal of Computer Vision - Special issue on a special section on visual surveillance
W4S: A real-time system detecting and tracking people in 2 1/2D
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Multi-Camera Multi-Person Tracking for EasyLiving
VS '00 Proceedings of the Third IEEE International Workshop on Visual Surveillance (VS'2000)
Towards Vision-Based 3-D People Tracking in a Smart Room
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
An Appearance-Based Body Model for Multiple People Tracking
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Multiple People Tracking Using an Appearance Model Based on Temporal Color
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Object Reacquisition Using Invariant Appearance Model
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Tracking multiple humans in crowded environment
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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Detecting, locating, and tracking people in a dynamic environment is important in many applications, ranging from security and environmental surveillance to assistance to people in domestic environments, to the analysis of human activities. To this end, several methods for tracking people have been developed using monocular cameras, stereo sensors, and radio frequency tags.In this paper we describe a real-time People Localization and Tracking (PLT) System, based on a calibrated fixed stereo vision sensor. The system analyzes three interconnected representations of the stereo data (the left intensity image, the disparity image, and the 3-D world locations of measured points) to dynamically update a model of the background; extract foreground objects, such as people and and rearranged furniture; track their positions in the world.The system can detect and track people moving in an area approximately 3 × 8 meters in front of the sensor with high reliability and good precision.