A Kalman filter approach for accurate 3-D motion estimation from a sequence of stereo images
CVGIP: Image Understanding
Active vision
Active vision
Real-time smooth pursuit tracking
Active vision
Active vision
Active tracking of foveated feature clusters using affine structure
International Journal of Computer Vision
Robot Control: The Task Function Approach
Robot Control: The Task Function Approach
Integrating Primary Ocular Processes
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Computer Vision and Image Understanding
Computer Vision and Image Understanding
Distributed sensor fusion for object tracking
RoboCup 2005
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This paper reports a visual tracking system that can track moving objects in real-time with a modest workstation equipped with a pan-tilt device. The algorithm essentially has three parts: (1) feature detection, (2) tracking and (3) control of the robot head. Corners are viewpoint invariant, hence being utilised as the beacon for tracking. Tracking is performed in two stages of Kalman filtering and affine transformation. A technique of reducing greatly the computational time for the correlaton is also described. The Kalman filter predicts intelligently the fovea window and reduced computation dramatically. The affine transformation deals with the unexpected events when there is partial occlusion.