摘要
为实现智能监控中有效的目标检测,提出了一种综合的动态背景提取和阴影去除方法。该方法应用多层次信息对混合高斯背景模型进行更新以获取高质量的彩色场景背景;同时,在前景提取过程中,结合RGB和HSI彩色信息对像素进行递进式分类,实现对阴影的去除。以此为基础实现的智能监控系统,实现了目标的跟踪与异常行为检测。经过不同场景的实验证明,本文所提方法能够满足实际应用的要求,具有良好的性能。
To achieve effective object detection in the intelligent surveillance, a comprehensive dynamic background difference and shadow removal method is proposed. Multi-level information is adopted to update the Gaussian Mixed Model to acquire color background image with high quality. Shadow is removed by a progressive pixel classification with proper RBG, Hue and Saturation information while extracting the foreground. Based on these results, object tracking and abnormal behavior detection are realized in an intelligent surveillance system. The experimental results with different scenes show that our method could satisfy the demand of practical applications with good performance.
出处
《计算机工程与科学》
CSCD
北大核心
2012年第12期98-104,共7页
Computer Engineering & Science
关键词
智能监控
背景提取
阴影去除
异常行为
intelligent surveillance
background extraction
shadow removal
abnormal behavior
