A GPU-Based Statistical Framework for Moving Object Segmentation: Implementation, Analysis and Applications

摘要

This paper describes a real-time implementation of a recently proposed background maintenance algorithm and reports the relative performances. Experimental results on dynamic scenes taken from a fixed camera show that the proposed parallel algorithm produces background images with an improved quality with respect to classical pixel-wise algorithms, obtaining a speedup of more than 35 times compared to CPU implementation. It is worth noting that we used both the GeForce 9 series (actually a 9800 GPU) available from the year 2008 and the GeForce 200 series (actually a 295 GPU) available from the year 2009. Finally, we show that this parallel implementation allows us to use it in real-time moving object detection application.