PTZ camera-based adaptive panoramic and multi-layered background model
Kang Xue, Gbolabo Ogunmakin, Yue Liu, Patricio Antonio Vela, Yongtian Wang · 2011
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.