Kinematic and Dynamic Simulation of Multibody Systems: The Real Time Challenge
Kinematic and Dynamic Simulation of Multibody Systems: The Real Time Challenge
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking Multiple Humans in Complex Situations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Mean-Shift Tracking via a New Similarity Measure
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Coupled Parametric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integration of Bayes detection with target tracking
IEEE Transactions on Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
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This paper presents a novel approach to track multiple articulated objects in a video sequence. The key idea is to define a model of the object using a set of geometrical primitives linked by physical constraints, and exploit physics engines to solve these constraints while the model adapts to the object under the influence of local mean-shift processes. This novel approach to object tracking has numerous advantages: the model provides rich geometric information about the object at the articulation level; multiple touching objects are implicitly distinguished using collision detection strategies; physics engines are able to efficicently manage both image-based and model-based constraints simultaneously for a neglectable computational cost, suggesting their potential interest for many more image processing applications.