Tracking and data association
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
Towards Vision-Based 3-D People Tracking in a Smart Room
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Tracking Multiple People with a Multi-Camera System
WOMOT '01 Proceedings of the IEEE Workshop on Multi-Object Tracking (WOMOT'01)
Towards a bayesian approach to robust finding correspondences in multiple view geometry environments
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Stochastic kinematic modeling and feature extraction for gait analysis
IEEE Transactions on Image Processing
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This paper presents a novel approach to the problem of estimating and tracking 3D locations of multiple targets in a scene using measurements gathered from multiple calibrated cameras. Estimation and tracking is jointly achieved by a newly conceived computational process, the Projective Kalman filter (PKF), allowing the problem to be treated in a single, unified framework. The projective nature of observed data and information redundancy among views is exploited by PKF in order to overcome occlusions and spatial ambiguity. To demonstrate the effectiveness of the proposed algorithm, the authors present tracking results of people in a SmartRoom scenario and compare these results with existing methods as well.