International Journal of Computer Vision
Pfinder: Real-Time Tracking of the Human Body
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
Towards Improved Observation Models for Visual Tracking: Selective Adaptation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Organized Integration of Adaptive Visual Cues for Face Tracking
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Real-Time Tracking Using Trust-Region Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Dynamic Bayesian Network Approach to Multi-cue based Visual Tracking
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Multi-cue-based CamShift guided particle filter tracking
Expert Systems with Applications: An International Journal
Multiview human pose estimation with unconstrained motions
Pattern Recognition Letters
Sensor management: a new paradigm for automatic video surveillance
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Computers and Electrical Engineering
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Multi-cue integration has been researched extensively for robust visual tracking. Researchers aim to use multiple cues under the probabilistic methods, such as Particle Filtering and Condensation. On the other hand, Color-based Mean-Shift has been addressed as an effective and fast algorithm for tracking color blobs. However, this deterministic searching method suffers from objects with low saturation color, color clutter in backgrounds and complete occlusion for several frames. This paper integrates multiple cues into Mean-Shift algorithm to extend its application areas of the fast and robust deterministic searching method. A direct multiple cues integration method with an occlusion handler is proposed to solve the common problems in color-based deterministic methods. Moreover, motivated by the idea of tuning weight of each cue in an adaptive way to overcome the rigidity of the direct integration method, an adaptive multi-cue integration based Mean-Shift framework is proposed. A novel quality function is introduced to evaluate the reliability of each cue. By using the adaptive integration method, the problem of changing appearance caused by object rotation can be solved. Extensive experiments show that this method can adapt the weight of individual cue efficiently. When the tracked color blob is invisible for human bodies' rotation, the color cue is compensated by motion cue. When the color blob becomes visible again, the color cue will become dominating as well. Furthermore, the direct-cue-integration method with an occlusion handler is combined with the adaptive integration method to extend the application areas of the adaptive method to full occlusion cases.