An efficient Real Time Implementation of Motion Estimation in Video Sequences on SOC

Abstract

Motion estimation is considered among the most famous and important applications in the field of computer vision. Indeed, in the last decade, the optical flow has become an alternative technique to estimate motion on successive frames. However, dense and precise estimates of the optical flow are usually costly in computing time. In this context, our approach is focused upon calculating the moving object's optical flow through the use of the Lucas-Kanade algorithm in real time which is implemented into Raspberry Pi 4. The efficiency of our real time implementation is demonstrated by the experimental results, hence showing better performances in comparison with the conventional calculation.