Title :
Keeping your eye on the ball: tracking occluding contours of unfamiliar objects without distraction
Author :
Toyama, Kentaro ; Hager, Gregory D.
Author_Institution :
Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA
Abstract :
Visual tracking is prone to distractions, where features similar to the target features guide the track away from its intended object. Global shape models and dynamic models are necessary for completely distraction-free contour tracking, but there are cases when component feature trackers alone can be expected to avoid distraction. We define the tracking problem in general and devise a method for local, window-based, feature trackers to track accurately in spite of background distractions. The algorithm is applied to a generic line tracker and a snake-like contour tracker which are then analyzed with respect to previous contour-trackers. We discuss the advantages and disadvantages of our approach and suggest that existing model-based trackers can be improved by incorporating similar techniques at the local level
Keywords :
computer vision; edge detection; feature extraction; optical tracking; computer vision; dynamic models; feature trackers; generic line tracker; global shape models; model-based trackers; occluding contour tracking; snake-like contour tracker; visual tracking; Algorithm design and analysis; Computational complexity; Computed tomography; Computer science; Computer vision; Image edge detection; Robustness; Shape; State-space methods; Target tracking;
Conference_Titel :
Intelligent Robots and Systems 95. 'Human Robot Interaction and Cooperative Robots', Proceedings. 1995 IEEE/RSJ International Conference on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
0-8186-7108-4
DOI :
10.1109/IROS.1995.525820