Currently, in the case of measuring a distance between an obstacle and a vehicle such as automobile, robot and unmanned aerial vehicle, a monocular vision technique has such detects as low accuracy, high missing rate and high misreporting rate, as compared with a radar distance-measurement technique and a binocular vision distance-measurement technique.
In the case of acquiring a speed of the obstacle relative to the vehicle, it is necessary to track and match depths of the obstacle measured twice, so as to acquire a correspondence between two pieces of sampling data of the same obstacle. For a conventional obstacle tracking algorithm, it is necessary to perform feature point matching and obstacle division on obstacle information acquired by two sampling operations. A feature point matching scheme, no matter on the basis of a depth map or an image, has such defects as large computation burden and low accuracy. Hence, it is impossible for the conventional algorithm to accurately determine the obstacle.
USPTO Backgrounds
USPTO Backgrounds