Dynamic Illumination Optical Flow Computing for Sensing Multiple Mobile Robots From a Drone
针对国际空中机器人竞赛任务，提出一种结合亮度恒常性松弛和强度归一化的光流算法，在照明变化环境下从无人机图像序列中检测和估计多个移动机器人的运动。
In this paper, we consider a motion sense problem motivated by the International Aerial Robotics Competition Mission-7, where an aerial robot is required to provide detection and estimation about mobile vehicles. Dense optical flow computing is employed first to provide a velocity field from image sequences. Then, region growing based on the optical flow field is used to extract moving objects on the background, and motion estimation is eventually achieved while both camera and objects are moving. In addition, classical optical flow techniques do not work in the competition since there may be illumination changes, such as flashlights and reflections in the arena. To deal with this problem, the procedures of the brightness constancy relaxation and intensity normalization are combined in the optical flow algorithm. Experimental results have demonstrated the robustness against varying illumination. The proposed approach can provide motion estimation results of acceptable accuracy for several benchmark data sets and image sequences generated with micro aerial vehicles.