Title :
Active contours for visual tracking: a geometric gradient based approach
Author :
Kumar, A. ; Yezzi, A. ; Kichenassamy, S. ; Olver, P. ; Tannenbaum, A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Minnesota Univ., Minneapolis, MN, USA
Abstract :
In this note, we analyze geometric active contour models from a curve evolution point of view and propose some modifications based on gradient flows relative to certain new metrics. This leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus the snake is attracted very naturally and efficiently to the desired feature. Moreover, we consider some 3-D active surface models based on these ideas
Keywords :
edge detection; feature extraction; optical tracking; 3D active surface models; curve evolution; geometric active contour models; geometric gradient-based approach; gradient flows; snake paradigm; visual tracking; Active contours; Books; Equations; Image edge detection; Image processing; Level set; Potential well; Shape; Solid modeling; Writing;
Conference_Titel :
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-2685-7
DOI :
10.1109/CDC.1995.479238