Title :
Zoom on target while tracking
Author :
Micheloni, C. ; Foresti, G.L.
Author_Institution :
Dept. of Mathematics & Comput. Sci., Udine Univ., Italy
Abstract :
In this paper, the problem of continuous tracking of moving objects with a PTZ camera is addressed. In particular, the problem of tracking moving objects during zoom phases is solved by using a feature clustering technique. In order to adopt such a method, we need, first, a step where during tracking with a pan&tilt camera we can identify the mobile objects in the monitored scene. Therefore, a set of good trackable features belonging to the selected target is extracted. In this research, we adopt a feature clustering method that is able to discriminate between features associated with the background and features associated with different moving objects. As a result, for each moving object, we have a set of correctly tracked features that is used to track the objects. Experiments have been performed on outdoor environments where either people or vehicles have been tracked. The results highlight how such a technique can be included in a more complex system able to maintain targets in the field of view of the camera, and to zoom on an object of interest when desired.
Keywords :
cameras; feature extraction; pattern clustering; statistical analysis; target tracking; feature clustering technique; features extraction; moving objects tracking; pan&tilt camera; target tracking; zoom phases; Cameras; Clustering methods; Computer science; Layout; Mathematics; Monitoring; Motion detection; Object detection; Object recognition; Target tracking;
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1530342