基于运动注意力融合模型的目标检测与提取算法

摘要

Aiming at the limitation of target detection and extraction algorithms under global motion scene, a target detection algorithm based on motion attention fusion model is proposed according to the motion attention mechanism. Firstly, the preprocess, such as accumulation and median filtering, is applied on the motion vector field. Then, according to the temporal and spatial characteristics of the motion vector, the motion attention fusion model is defined to detect moving target. Finally, the edge of the video moving target is extracted accurately by the morphologic operation and the edge tracking algorithm. The experimental results of different global motion video sequences show the proposed algorithm has better veracity and speedup than other algorithms.%针对全局运动场景下目标检测与提取方法的局限性，文中根据运动注意力形成机理，构建一种运动注意力时-空融合模型用于运动目标的检测与提取。该算法首先对运动矢量场进行叠加和滤波等预处理。然后根据运动矢量在时间和空间上的变化特点定义运动注意力融合模型，并采用该模型检测运动目标区域。最后利用形态学和边界跟踪方法对目标区域进行精确化提取。根据多个不同全局运动视频场景的测试结果，显示该算法比其它算法具有更好的准确性和实时性。