A framework for spatiotemporal control in the tracking of visual contours
International Journal of Computer Vision
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Indoor Monitoring Via the Collaboration Between a Peripheral Sensor and a Fovea1 Sensor
VS '98 Proceedings of the 1998 IEEE Workshop on Visual Surveillance
The estimation of the gradient of a density function, with applications in pattern recognition
IEEE Transactions on Information Theory
A Mathematical Model for Computer Image Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition
Pearson-based mixture model for color object tracking
Machine Vision and Applications
An Automated Refereeing and Analysis Tool for the Four-Legged League
RoboCup 2006: Robot Soccer World Cup X
Multi-target tracking for flower counting using adaptive motion models
Computers and Electronics in Agriculture
Target tracking and localization of binocular mobile robot using camshift and SIFT
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
A swarm-intelligence based algorithm for face tracking
International Journal of Intelligent Systems Technologies and Applications
Combined Motion and Appearance Models for Robust Object Tracking in Real-Time
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Mean Shift tracking with multiple reference color histograms
Computer Vision and Image Understanding
Object tracking with self-updating tracking window
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
Getting robust observation for single object tracking: a statistical Kernel-based approach
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
3D fast spatial filtering method
International Journal of Computational Vision and Robotics
A hybrid motion and appearance prediction model for robust visual object tracking
Pattern Recognition Letters
Hi-index | 0.10 |
We propose a new adaptive model update mechanism for the real-time mean shift blob tracking. Since the Kalman filter has been used mainly for smoothing the object trajectory in the tracking system, it is novel for us to use adaptive Kalman filters for filtering object kernel histogram so as to obtain the optimal estimate of object model. The acceptance of the object estimate for the next frame tracking is determined by a robust criterion, i.e. the result of hypothesis testing with the samples from the filtering residuals. Therefore, the tracker can not only update object model in time but also handle severe occlusion and dramatic appearance changes to avoid over model update. We have applied the proposed method to track real object under the changes of scale and appearance with encouraging results.