Robust Detection of Moving Objects in Video

Motion segmentation is an important process for separating moving objects from the background. Common methods usually assume fixed camera, other approaches exist as well, but they are usually very computational intensive. This work presents an approach for scene segmentation to regions with coherent motion, which works faster than similar methods and it is capable of online processing with no prior knowledge of objects or camera. The main assumption is that the points belonging to a single objects are moving together and this applies as well in the opposite direction. The proposed method is based on tracking of feature points and searching for groups with similar motion by using RANSAC-based algorithm. Short-range repair of broken tracks is applied to increase the overall robustness of tracking. Found clusters are subsequently processed to represent separate moving objects