Research Of Moving Object Detection And Tracking Algorithms Based On Fish Eye Camera

With the development and progress of society, more and more vehicles are on the road, so that traffic accident often occur, so how to effectively reduce the traffic accident and reduce the collision of vehicles and pedestrians, immediately warning motorists to avoid of collisions, it has become the focus of attention. In particular, drunk driving into the penalty has been introduced into the bill of country, it shows that traffic safety has more importance. DAS (Driver Assistance System) technology has become increasingly important. Detecting and tracking is an important link of DAS technology, how to effectively improve the levels of results on the detecting and tracking has become a key issue.It’s restricted the veracity and instantaneity of Campaign target that is complex background, the diversity of moving objects(including rigid people, moving vehicles and animals and so on),Blocking out that is aroused by pedestrians or vehicles, change of weather and lighter and other factors.In this paper, we get the external environment information by means of on-board fish-eye camera. From the real practical point of view, we found moving target detection and tracking system.In the moving target detection system, this paper proposes a hierarchical ego-motion compensation method to eliminate the impact of camera motion. Through the moving target detection, it may detect the area of moving targets, then improved particle filter algorithm is used to track the moving object, and use color histogram to judge of the tracking result in the real time, judge that the tracking object is the moving object in the front of frame, if effectively reduce error detection rate.The proposed moving object detection and tracking algorithms were tested with a large number of different scenarios in the test sets, and the results shown that the proposed algorithms were robust and exact.