FPGA-based implementation of a low cost and area real-time motion detection

High-level computer vision tasks such as robot navigation, collision avoidance, path planning, and video surveillance require detection of the moving objects in the surrounding environment at real time. In the first part of this paper, a new algorithm based on a multi-modal distribution is presented to detect the moving objects in image sequence taken from a static camera with a small number of calculations. It is primarily composed of linear operations that are easily implemented in hardware and there is no iteration for any explicit coarse-to-fine control strategy. These properties make the real time flow of data possible through the hardware. We show that the elapsed time per frame is reduced by applying the proposed algorithm. For the second part, an FPGA-based implementation is described for the proposed algorithm at a very high frame rate that reaches to 1130 fps in a single low cost FPGA chip, which is adequate for most real-time vision applications. We show that the area of the implemented architecture can be reduced by 13.4%.