Moving target detection based on the properties of corners

2012 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2012-12-01 DOI:10.1109/ROBIO.2012.6490990

Bin Leng, Qing He, Dewen Zeng, Jian Cao, Guan Guan, Hongwei Xu, Xiaoling Wu, Weimin Zheng

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引用次数: 5

Abstract

In video surveillance, there are a variety of random disturbances on moving target detection, such as trees sway, camera shake. In order to eliminate these disturbances, this paper presents a novel moving object detection algorithm based on the properties of corner points. Firstly, this paper uses Harris algorithm to detect corner on the video image, and then proposes a novel indicator, Inter-frame Regional Corners Difference, to select the candidate grids of foreground. In this way, the static and slight shaking background is recognized. Secondly, this paper makes use of Horn and Schunck's optical flow algorithm to build the optical flow field of grids that are the candidates of foreground, and extracts the moving target by some velocity constraint of the horizontal and vertical direction. In virtue of the different dynamic properties of background and moving target, the dynamic background can be eliminated. The experimental results show that our algorithm can accurately extract moving target and can meet the needs of real-time processing with strong anti-jamming.

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基于角点特性的运动目标检测

在视频监控中，对运动目标检测存在各种随机干扰，如树木晃动、摄像机晃动等。为了消除这些干扰，本文提出了一种基于角点特性的运动目标检测算法。本文首先利用Harris算法对视频图像进行角点检测，然后提出一种新的指标帧间区域角点差来选择前景的候选网格。通过这种方法，可以识别出静态和轻微抖动的背景。其次，利用Horn和Schunck的光流算法构建前景候选网格的光流场，通过水平方向和垂直方向的速度约束提取运动目标;利用背景和运动目标不同的动态特性，可以消除动态背景。实验结果表明，该算法能够准确提取运动目标，满足实时处理的需要，抗干扰能力强。

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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来源期刊

2012 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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