Motion detection with low cost hardware for PTZ cameras

Abstract

Pan-tilt-zoom (PTZ) cameras are well suited to motion detection and tracking objects due to their mobility. Motion detection approaches based on background difference have been the most used with fixed cameras because of the high quality of the achieved segmentation. However, time requirements and high costs prevent most of the algorithms proposed in literature from exploiting the background difference with PTZ cameras in real world applications, such as automatic surveillance. This paper presents a new algorithm to detect moving objects within an area covered by a PTZ camera while it is panning, tilting or zooming in or out. The low computational demands of the algorithm allow for its deployment to a Raspberry Pi microcontroller-based board, which enables the design and implementation of a low-cost monitoring system that is able to perform real-time image processing. First, our system works offline to estimate the parameters of the motion detection model, which are written on the Raspberry Pi memory. Second, motion detection is performed online by the microcontroller. Experimental results using different moving objects classifiers (FANN, KNN, and SVM) confirm the good performance of this approach in terms of different classification performance measures (accuracy, F-measure, AUC, and sample processing time).