The high speed attitude maneuver of Unmanned Aerial Vehicle (UAV) always causes large motion between adjacent frames of the video stream produced from the camera fixed on the UAV body, which will severely disrupt the performance of image object tracking process. To solve this problem, this paper proposes a method that using a gyroscope fixed on the camera to measure the angular velocity of camera, and then the object position’s substantial change in the video stream is predicted. We accomplished the object tracking based on template matching. Experimental result shows that the object tracking algorithm’s performance is improved in its efficiency and robustness with embedded gyroscope information.
This paper proposes a novelty dense stereo matching method based on TC-MST (Threshold Constrained Minimum Spanning Tree), which aims to improve the accuracy of distance measuring. Due to the threshold has a great impact on the results of image segments, to select a better threshold, we adopt iteration threshold method. And then we uses MST to calculate the cost aggregation, and utilize the winner-take-all algorithm for the cost aggregation to obtain the disparity. Finally the method proposed is used in a distance measuring system. The experiment results show that this method improves the distance measuring accuracy compared with BM (block matching).