Generalizing the Lucas-Kanade algorithm for histogram-based tracking
Pattern Recognition Letters
A spatial-color mean-shift object tracking algorithm with scale and orientation estimation
Pattern Recognition Letters
Timed trajectory generation using dynamical systems: Application to a Puma arm
Robotics and Autonomous Systems
Mean Shift Parallel Tracking on GPU
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Multiple people labeling and tracking using stereo for human computer interaction
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Motion observability analysis of the simplified color correlogram for visual tracking
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Tracking people in video sequences using multiple models
Multimedia Tools and Applications
Object tracking using parallel local colour histogram method
International Journal of Computational Vision and Robotics
A compact auto color correlation using binary coding stream for image retrieval
Proceedings of the 15th WSEAS international conference on Computers
A simple oriented mean-shift algorithm for tracking
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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Color histogram based representations have been widely used for blob tracking. In this paper, a new color histogram based approach for object representation is proposed. By using a simplified version of color correlogram as object feature, spatial information is incorporated into object representation, which allows variations of rotation to be detected throughout the tracking therefore rotational objects can be more accurately tracked. The gradient decent method mean shift algorithm is adopted as the central computational module and further extended to a 3D domain to find the mostprobable target position and orientation simultaneously. The capability of the tracker to tolerate appearance changes like orientation changes, small scale changes, partial occlusions and background scene changes is demonstrated using real image sequences.