Title :
Automatic selection of control points for deformable-model-based target tracking
Author :
Pavlidis, I. ; Papanikolopoulos, N.P.
Author_Institution :
Dept. of Comput. Sci., Minnesota Univ., Minneapolis, MN, USA
Abstract :
A novel curve segmentation algorithm for determining control points for deformable-model-based target tracking is proposed. The algorithm is parameterless enabling a fully-fledged automated tracking regardless of the shape of the object being tracked. Compared with other curve segmentation algorithms, it selects a minimal number of control points that yet deliver a superior shape description. The algorithm is comparatively tested with other curve segmentation algorithms in a variety of characteristic target outlines
Keywords :
image segmentation; robot vision; target tracking; tracking; control points; curve segmentation algorithm; deformable-model-based target tracking; fully-fledged automated tracking; shape description; Artificial intelligence; Automatic control; Deformable models; Intelligent robots; Laboratories; Robot vision systems; Robotics and automation; Shape control; Target tracking; Testing;
Conference_Titel :
Robotics and Automation, 1996. Proceedings., 1996 IEEE International Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
0-7803-2988-0
DOI :
10.1109/ROBOT.1996.509155