Title :
PTZ camera-based adaptive panoramic and multi-layered background model
Author :
Xue, Kang ; Ogunmakin, Gbolabo ; Liu, Yue ; Vela, Patricio A. ; Wang, Yongtian
Abstract :
In this paper, we present a novel approach for constructing an adaptive panoramic and multi-layered background model for Pan-tilt-zoom (PTZ) camera that provides fast registration of the observed frame and localizes the foreground targets with arbitrary camera position and scale (optical zoom). Our method consists of two stages. (1) An adaptive panoramic background mixture model is generated off-line for foreground detection. (2) A layered correspondence is generated off-line from frames captured at different optical zoom values of the camera, and a correspondence propagation method is used to register the observed frame with the panoramic background online. We demonstrate the advantages of the proposed adaptive panoramic and multi-layered background model within wide field of view (FOV) and over large scale range.
Keywords :
cameras; image registration; object detection; FOV; adaptive panoramic model; fast registration; field of view; foreground detection; multi-layered background model; pan-tilt-zoom camera; Adaptation models; Cameras; Computational modeling; Computer vision; Conferences; Feature extraction; Surveillance; Object detection; PTZ camera; multi-layered propagation; panoramic background;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6116280