摘要
为检测无人机视频中的地面运动目标,提出了一种运动和颜色信息相结合的算法.采用前向运动历史图像来增强独立运动信息和抑制背景噪声,确保完整分割出候选运动区域;提出一种迭代的、基于局部颜色分布比对的方法,去除候选区域中的背景像素,以更准确地提取单个运动目标.算法不仅节约了计算量,还有效降低了误检和漏检的可能性.多组无人机视频的实验结果表明了所提算法的高效性和鲁棒性.
To detect moving objects from videos taken by unmanned aerial vehicles, an approach using motion .and color cues was proposed. It adopted the forward motion history image to enhance the independent moving information and suppress the noises in background areas, enabling the candidate moving regions to be extracted entirely. Then, an iterative local color distribution comparison based the method was developed to remove the background pixels contained by each candidate region, insuring each moving object to be extracted precisely. Thus, the cost of computation is saved, and the miss rate and false alarm rate can be cut down prominently. Experimental results with several aerial videos demonstrate the performance and the robustness of the proposed method.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2012年第2期263-267,272,共6页
Journal of Beijing University of Aeronautics and Astronautics
关键词
航空视频分析
运动目标检测
前向运动历史图像
局部颜色分布比对
aerial video analysis
moving object detection
forward motion history image
local colordistribution comparison