Title :
Tracking static local kernels within image frames
Author :
Wang, Xin ; Wang, Jin
Author_Institution :
Sch. of Railway Power & Electr. Eng., Nanjing Railway Inst. of Technol., Nanjing, China
Abstract :
We describe an active contour based local energy minimization point distribution, behavior of orientation, relaxation iterative algorithm that estimates feature points of static target in image sequence. In our approach, we build a contour model of a target to get some of low-energy points kernels. The use of snake based line model results in more reliable convergence of the point local energy minimization. The algorithm uses auto-relation relation to give the behavior of orientation in a local kernel´s window. It uses local window-based probability method to refine the current corresponding relations of scene kernels. Results are illustrated on real outdoor image sequence.
Keywords :
image sequences; iterative methods; probability; active contour based local energy minimization point distribution; autorelation algorithm; image frames; iterative algorithm; local energy minimization; local window-based probability method; low energy point kernels; real outdoor image sequence; static local kernels tracking; target contour model; Analytical models; Radio access networks; Target tracking; Image; Interest Points; Relaxation Iterative; Snake;
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
DOI :
10.1109/ICCSIT.2010.5563628