摘要
针对视频安全监控问题,提出一种实时的遗失目标检测算法。首先,帧间差分用于获取像素级运动特性,并构造双重背景用于检测双重前景。而后,将像素级特性及双重前景综合以维持双重背景的更新。最后,通过累加证据图像来处理实际应用中的虚警和遮挡问题并证实遗失目标。在不同视频序列下的实验表明该算法能够有效地从嘈杂的场景中检测出遗失目标。此外,对于352×288的序列而言,该算法的运行速度达到约54帧/s,能够满足实时的监控任务需求。
To solve the problem of video-based security surveillance, a real-time method for abandoned object detection is proposed. First, frame-to-frame difference is used to obtain the pixel-wise properties of motion, and two backgrounds are constructed to detect dual foregrounds. Then, the pixel-wise properties and both foregrounds are integrated to maintain the dual backgrounds. Since the false alarms and occlusions necessarily occur and degrade the detection performance in practical applications, an evidence image is aggregated to validate the abandoned object. Experiments on several different video sequences demonstrate that the proposed method is effective in detecting abandoned objects from cluttered scenes. In addition, this method runs around 54 frames per second for a sequence with an image resolution of 352-288, which can be applied to real-time surveillance tasks.
出处
《光电工程》
CAS
CSCD
北大核心
2009年第7期36-40,共5页
Opto-Electronic Engineering
基金
国家863计划高新技术预研课题资助项目(2003AA823050)
关键词
视频监控
遗失目标检测
背景更新
证据图像
实时处理
video surveillance
abandoned object detection
background update
evidence image
real-time processing
