摘要
运动目标检测是视频分析领域的关键技术之一,针对目前全局运动场景下目标检测算法的局限性,该文提出一种多尺度运动注意力融合的目标检测算法,为目标检测问题提供了新思路。该算法通过时-空滤波去除运动矢量场噪声,根据运动注意力形成机理定义运动注意力模型;为提高注意力计算的准确性,定义了目标像素块的测度公式,采用D-S证据理论对多尺度空间运动注意力进行决策融合,最终获取运动目标区域位置。多个不同高清视频序列的测试结果表明,该文算法在全局运动场景中能准确对目标进行检测定位,从而有效克服了现有算法的局限性。
The detection to target in motion is a key technology in video analysis. This paper proposes a target detection algorithm based on a multi-scale motion attention analysis, which provides a new method for motion target detection under a global motion scene. Firstly, the noise of motion vector field is removed by filter, and according to the mechanism of visual attention, spatial-temporal motion attention model is built; then the trust degree of motion vector is suggested on the basis of validity analysis of motion vector, and decision fusion of multi-scale motion attention is accomplished by D-S theory for detecting the region of motion target. The test results of different videos show that the algorithm is able to detect precisely targets under a global motion scene, thus effectively overcoming the limitations of the traditional algorithms.
出处
《电子与信息学报》
EI
CSCD
北大核心
2014年第5期1133-1138,共6页
Journal of Electronics & Information Technology
基金
国家自然科学基金(61001140)
陕西省教育厅产业化培育项目(2012JC19)
西安市技术转移促进工程重大项目(CX12166)资助课题
关键词
目标检测
运动注意力
融合
全局运动场景
Target detection
Motion attention
Fusion
Global motion scene