Image segmentation based on object oriented mapping parameter estimation
Signal Processing
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Occlusion and Dense Motion Fields in a Bidirectional Bayesian Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking Multiple Humans in Complex Situations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking People through Occlusions
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Real-Time Multiple Objects Tracking with Occlusion Handling in Dynamic Scenes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Fixed Point Probability Field for Complex Occlusion Handling
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
A hybrid blob- and appearance-based framework for multi-object tracking through complex occlusions
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Tracking multiple humans in crowded environment
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Robust online appearance models for visual tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast occluded object tracking by a robust appearance filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple objects tracking by color-based methods
ISCGAV'08 Proceedings of the 8th conference on Signal processing, computational geometry and artificial vision
Self-localization and stream field based partially observable moving object tracking
EURASIP Journal on Advances in Signal Processing - Special issue on signal processing advances in robots and autonomy
Multi-cue Based Visual Tracking in Clutter Scenes with Occlusions
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Multiple and variable target visual tracking for video-surveillance applications
Pattern Recognition Letters
Depth assisted occlusion handling in video object tracking
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Visual tracking of multiple targets by multi-bernoulli filtering of background subtracted image data
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
A probabilistic integrated object recognition and tracking framework
Expert Systems with Applications: An International Journal
Visual tracking of numerous targets via multi-Bernoulli filtering of image data
Pattern Recognition
Investigation on tracking system for real time video surveillance applications
Proceedings of the CUBE International Information Technology Conference
Incorporation of GPS and IP camera for people tracking
GPS Solutions
Radar-based road-traffic monitoring in urban environments
Digital Signal Processing
Target Tracking Using Multiple Patches and Weighted Vector Median Filters
Journal of Mathematical Imaging and Vision
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To track multiple objects through occlusion, either depth information of the scene or prior models of the objects such as spatial models and smooth/predictable motion models are usually assumed before tracking. When these assumptions are unreasonable, the tracker may fail. To overcome this limitation, we propose a novel online sample based framework, inspired by the fact that the corresponding local parts of objects in sequential frames are always similar in the local color and texture features and spatial features relative to the centers of objects. Experimental results illustrate that the proposed approach works robustly under difficult and complex conditions.