基于对称差分和背景减的运动目标检测

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。

Moving object detection algorithm based on symmetrical-differencing and background subtraction

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.