Efficient Moving Object Detection for Lightweight Applications on Smart Cameras

Recently, the number of electronic devices with smart cameras has grown enormously. These devices require new, fast, and efficient computer vision applications that include moving object detection strategies. In this paper, a novel and high-quality strategy for real-time moving object detection by nonparametric modeling is presented. It is suitable for its application to smart cameras operating in real time in a large variety of scenarios. While the background is modeled using an innovative combination of chromaticity and gradients, reducing the influence of shadows and reflected light in the detections, the foreground model combines this information and spatial information. The application of a particle filter allows to update the spatial information and provides a priori knowledge about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results. The quality of the results and the achieved computational efficiency show the suitability of the proposed strategy to enable new applications and opportunities in last generation of electronic devices.