摘要
通过对视频运动对象特点的分析,提出一种针对静态场景的运动目标检测算法。该算法采用一种改进的时间平均法初始化背景,在有目标的情况下也能构建出可靠的背景,并融合背景减法和多重对称差分法对背景进行自适应更新。实验结果证明,该算法计算简单,对光线变化具有适应性,能够完整地提取运动目标,改善了运动目标的检测效果,具有一定的鲁棒性。
An algorithm for moving object detection with a static background is proposed by analyzing characteristic of movement objects in video. The algorithm uses improved time-averaged method to initialize background, it can obtain reliable background in the condition of having moving objects. During background updating, the paper combines background subtraction method and multi-symmetrical-differencing. Experimental results show that the proposed algorithm is quick, robust, adaptive to illumination changes and it improves the effect of moving object detection.
出处
《计算机工程与应用》
CSCD
2014年第13期158-162,共5页
Computer Engineering and Applications
基金
国家自然科学基金(No.60835004)
关键词
运动目标检测
自适应背景
多重对称差分
光线突变
moving object detection
adaptive background
multi-symmetrical-differencing
sudden illumination changes