Robust environmental change detection using PTZ camera via spatial-temporal probabilistic modeling

This paper proposes a novel procedure for detecting environmental changes by using a pan-tilt-zoom (PTZ) camera. Conventional approaches based on pixel space and stationary cameras need time-consuming image registration to yield pixel statistics. This work proposes an alternative approach to describe each scene with a Gaussian mixture model (GMM) via a spatial-temporal statistical method. Although details of the environment covered by the camera are lost; this model is efficient and robust in recognizing scene and detecting scene changes in the environment. Moreover, the threshold selection for separating different environmental changes is convenient by using the proposed framework. The effectiveness of the proposed method is demonstrated experimentally in an office environment.