Title :
Homographic line generation and transformation technique for dynamic object association
Author :
Shung Han Cho ; Hong, Sangjin ; Cho, Shung Han
Author_Institution :
Dept. of Electr. & Comput. Eng., Stony Brook Univ., Stony Brook, NY
Abstract :
Object association among multiple cameras is an important capability for maintaining consistent view of surroundings. This is necessary in many applications such as tracking and surveillance. In this paper, we present a dynamic homographic line generation technique supporting the camera movement for object association in the multiple visual sensors network. The conventional method uses the globally defined homographic lines or the feature based methods for the object association. However, these methods restrict the camera movement (i.e., panning, tilting and zooming) required for efficient and effective association in the autonomous surveillance system. The proposed method uses the table based compensation for non-ideal camera parameters to support the camera movement. Lastly, two possible application models are simulated with the proposed technique.
Keywords :
cameras; target tracking; video surveillance; wireless sensor networks; autonomous surveillance system; dynamic object association; homographic line generation; multiple cameras; multiple visual sensors network; nonideal camera parameters; target tracking; transformation technique; Acoustic distortion; Acoustic noise; Acoustic sensors; Application software; Cameras; Labeling; Lenses; Reverberation; Surveillance; Target tracking;
Conference_Titel :
Machine Learning for Signal Processing, 2008. MLSP 2008. IEEE Workshop on
Conference_Location :
Cancun
Print_ISBN :
978-1-4244-2375-0
Electronic_ISBN :
1551-2541
DOI :
10.1109/MLSP.2008.4685492