Fast and Efficient Extraction of Moving Objects

M. Javan, S.M. Bouzari, A. Salahi
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引用次数: 0

Abstract

Objects in video sequence have attracted much attention due to their role in many applications such as tracking, surveillance, and video compression. In this paper, we propose an efficient and accurate method for detecting moving objects in a video sequence. Motion information is used to detect primitive object candidates, so global motion and optical flow estimation is the first step in this algorithm. The estimation is done with our proposed method which is a modification of Horn-Schunck method. The proposed method for optical flow estimation is very fast and needs less iterations than does the original one (Horn-Schunk). Those areas which have different motion from global motion, according to efficient criterion, are marked as object candidates. The spatial information is used to extract the final object. The experimental results show the efficiency and accuracy of proposed algorithm.
快速有效地提取运动物体
视频序列中的对象由于在跟踪、监控、视频压缩等应用中发挥着重要的作用而备受关注。本文提出了一种高效、准确的视频序列运动目标检测方法。该算法利用运动信息检测原语候选目标,因此全局运动和光流估计是该算法的第一步。该方法是对Horn-Schunck方法的一种改进。本文提出的光流估计方法比原方法(Horn-Schunk)迭代次数少,速度快。根据有效准则,将运动与全局运动不同的区域标记为候选对象。空间信息用于提取最终目标。实验结果表明了该算法的有效性和准确性。
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