Title :
Model-Free, Statistical Detection and Tracking of Moving Objects
Author_Institution :
Inst. of Computational Visualistics, Univ. of Koblenz, Germany
Abstract :
A novel statistical approch for detection and tracking of objects is presented here, which uses both edge and color information in a particle filter. The approach does not need any prior models of the objects of interest or of the scene. It starts with homogenous regions as tracking primitives and creates complex objects by merging similar moving regions. Even partially occluded objects in a sequence captured by a moving camera can be tracked efficently and robust.
Keywords :
cameras; edge detection; filtering theory; image colour analysis; image sequences; object detection; statistical analysis; tracking; color information; edge information; image sequence; moving camera; moving object tracking; partially occluded object; particle filter; statistical detection; Filtering; Image edge detection; Layout; Object detection; Particle filters; Particle tracking; Robustness; Sampling methods; Shape control; Visualization;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312486
