Detection and tracking of moving objects by fuzzy textures

S. M. Roomi, S. A. Karpaga
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引用次数: 2

Abstract

Video surveillance plays a prominent role in law enforcement, personal safety, traffic control, resource planning and security of assets, etc. The need for such systems is increasing every day, with a number of surveillance cameras deployed in public places to analyze moving objects. Automatic video surveillance system can enforce the security in the monitored area without requiring the continuous attention of human operators. For such systems, moving object detection and tracking in dynamic backgrounds such as waving trees, oceans etc... is still a challenging task. Noise in the foreground due to dynamic background condition should be removed effectively for efficient tracking of the moving objects. In this paper, objects present in dynamic backgrounds are detected using a simple and robust fuzzy texture based analysis of the video sequences. Then the detected moving object is tracked using the mean shift tracking algorithm to describe the object's direction of motion. The proposed method effectively detects the moving objects and describes the object's motion.
基于模糊纹理的运动物体检测与跟踪
视频监控在执法、人身安全、交通管控、资源规划、资产保障等方面发挥着突出的作用。对这类系统的需求每天都在增加,在公共场所部署了许多监控摄像头来分析移动物体。自动视频监控系统可以在不需要操作人员持续关注的情况下加强被监控区域的安全。对于这样的系统,移动目标的检测和跟踪在动态背景,如波浪树,海洋等…仍然是一项具有挑战性的任务。为了有效地跟踪运动目标,需要有效地去除动态背景条件下前景中的噪声。在本文中,使用基于视频序列的简单鲁棒模糊纹理分析来检测动态背景中的目标。然后利用mean shift跟踪算法对检测到的运动目标进行跟踪,以描述目标的运动方向。该方法可以有效地检测运动物体并描述物体的运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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