Moving Object Detection in Video Streams Received from a Moving Camera

Detection of moving objects in a video stream received from a moving camera is difficult computer vision task, because the motion of the camera blends with the motion of the objects in the scene. In order to tackle this problem, we propose a method based on optical flow calculation and Delaunay triangulation. Given a sequence of frames, firstly, we extract the corner feature points using ORB algorithm and compute optical flow vectors at the extracted feature points. Secondly, we separate the optical flow vectors using K-Means clustering method. Third, we classify each cluster into camera and object motion using its mean scatter value. Finally, we represent the moving object using Delaunay triangulation.