A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi Feature Path Modeling for Video Surveillance
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Image alignment and stitching: a tutorial
Foundations and Trends® in Computer Graphics and Vision
Trajectory analysis in natural images using mixtures of vector fields
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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This paper presents a new model for trajectories in video sequences using mixtures of motion fields. Each field is described by a simple parametric model with only a few parameters. We show that, despite the simplicity of the motion fields, the overall model is able to generate complex trajectories occuring in video analysis.