基于角点的动态背景下运动目标检测算法改进  

Improvement of angular point based moving object detection algorithm in dynamic background

作　　者：肖春明[1] 

机构地区：[1]内蒙古警察职业学院,内蒙古呼和浩特010051

出　　处：《现代电子技术》2016年第7期66-70,共5页Modern Electronics Technique

摘　　要：由于动态摄像机行为造成了背景模糊等问题,结合角点矩特征的全局运动估计算法,将最大类间方差法引入RANSAC估计算法,对常用的RANSAC算法进行改进。在目标检测过程中,利用基于差分相乘原理的运动目标检测算法实现了运动目标的检测定位。针对获取到目标位置的后续帧序列的目标检测,提出了基于改进的奇异值分解的角点匹配的运动目标检测算法。实验表明,提出的算法对于背景发生变化的场景,能达到较好的背景运动补偿效果,在随后测量的动态背景状态下,可以准确检测后续帧序列的运动目标,并且具有良好的鲁棒性。To resolve the indistinct background problem caused by dynamic camera behavior,and in combination with the global motion estimation algorithm of angular point distance feature,the maximum interclass variance method is introduced into the RANSAC estimation algorithm to improve the common RANSAC algorithm. The moving object detection algorithm based on difference multiply principle is used to detect and locate the moving object in object detection process. Aiming at the object detection of follow-up frame sequence of the obtained object location,the moving target detection algorithm based on angular point marching of improved singular value decomposition is proposed. The experimental results demonstrate that the proposed algorithm has good background motion compensation effect in dynamic background,and can accurately detect the moving target of the follow-up frame sequence in the subsequent measured dynamic background measurement. The algorithm has good robustness.

关 键 词：目标检测 全局运动估计 角点 奇异值分解 

分 类 号：TN941.1[电子电信—信号与信息处理]