基于运动增强和颜色分布比对的运动目标检测

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.

Moving object detection using motion enhancement and color distribution comparison

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.