物理学报2017，Vol.66Issue(8)：107-115,9.DOI:10.7498/aps.66.084203
动态背景下基于光流场分析的运动目标检测算法
Moving ob ject detection based on optical flow field analysis in dynamic scenes
摘要
Abstract
To overcome the limitation of existing algorithms for detecting moving objects from the dynamic scenes, a fore-ground detection algorithm based on optical flow field analysis is proposed. Firstly, the object boundary information is determined by detecting the differences in optical flow gradient magnitude and optical flow vector direction between foreground and background. Then, the pixels inside the objects are obtained based on the point-in-polygon problem from computational geometry. Finally, the superpixels per frame are acquired by over-segmenting method. And taking the superpixels as nodes, the Markov Random field model is built, in which the appearance information fitted by Gaussian Mixture Model is combined with spatiotemporal constraints of each superpixel. The final foreground detection result is obtained by finding the minimum value of the energy function. The proposed algorithm does not need any priori assumptions, and can effectively realize the moving object detection in dynamic and stationary background. The exper-imental results show that the proposed algorithm is superior to the existing state-of-the-art algorithms in the detection accuracy, robustness and time consuming.关键词
动态背景/运动目标检测/光流场分析/马尔可夫随机场模型Key words
dynamic scene/moving object detection/optical flow field analysis/Markov random field model引用本文复制引用
崔智高,王华,李艾华,王涛,李辉..动态背景下基于光流场分析的运动目标检测算法[J].物理学报,2017,66(8):107-115,9.基金项目
国家自然科学基金(批准号:61501470)资助的课题. Project supported by the National Natural Science Foundation of China (Grant No.61501470). （批准号:61501470）
