A local-motion-based probabilistic model for visual tracking
Pattern Recognition
Surveillance Robot Utilizing Video and Audio Information
Journal of Intelligent and Robotic Systems
Graph-based transductive learning for robust visual tracking
Pattern Recognition
Occlusion reasoning for tracking multiple people
IEEE Transactions on Circuits and Systems for Video Technology
Adaptable Neural Networks for Objects' Tracking Re-initialization
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
An incremental Bhattacharyya dissimilarity measure for particle filtering
Pattern Recognition
Visual Tracking via Particle Filtering on the Affine Group
International Journal of Robotics Research
Semi adaptive appearance models for lip tracking
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Multimedia Tools and Applications
Segmenting and tracking multiple objects under occlusion using multi-label graph cut
Computers and Electrical Engineering
Tree-structured image difference for fast histogram and distance between histograms computation
Pattern Recognition Letters
Particle Filtering with Region-based Matching for Tracking of Partially Occluded and Scaled Targets
SIAM Journal on Imaging Sciences
A compact association of particle filtering and kernel based object tracking
Pattern Recognition
Visual tracking via dynamic tensor analysis with mean update
Neurocomputing
An Efficient Particle Filter---based Tracking Method Using Graphics Processing Unit (GPU)
Journal of Signal Processing Systems
Block covariance based l1 tracker with a subtle template dictionary
Pattern Recognition
Game-theoretical occlusion handling for multi-target visual tracking
Pattern Recognition
A survey of appearance models in visual object tracking
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Scale modification through particle distribution in colour based tracking
Proceedings of the 10th European Conference on Visual Media Production
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We propose a similarity measure based on a spatial-color mixture of Gaussians (SMOG) appearance model for particle filters. This improves on the popular similarity measure based on color histograms because it considers not only the colors in a region but also the spatial layout of the colors. Hence, the SMOG-based similarity measure is more discriminative. To efficiently compute the parameters for SMOG, we propose a new technique with which the computational time is greatly reduced. We also extend our method by integrating multiple cues to increase the reliability and robustness. Experiments show that our method can successfully track objects in many difficult situations.