An Adaptive Object Detection Scope Algorithm Based on SIFT

Yuanyuan Lu, Xiangyang Xu, Y. Dai, Bin Zheng
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引用次数: 5

Abstract

For camera movement causes moving objects detecting and tracking problems under complex background, we propose an adaptive object detection scope algorithm based on SIFT features. Firstly, let camera stationary and obtain three images to detect the moving object by using three-frame-difference method, then extract the object SIFT features. Secondly, according to the location and displacement of the object in the dynamic background, we determine the detection scope which matches the object well and obtain the minimum rectangle which can surround the right matching points in the detection scope, and then update the object template. The algorithm avoids the analysis of the complex relative motion between the object and the background, and reduces mismatch points and the calculation amount. This algorithm can quickly and accurately track the object without occlusion, and performs robust in small occlusion case.
基于SIFT的自适应目标检测范围算法
针对摄像机运动引起的复杂背景下运动目标的检测和跟踪问题,提出了一种基于SIFT特征的自适应目标检测范围算法。首先,让摄像机静止,利用三帧差分法获取三幅图像检测运动目标,然后提取目标SIFT特征。其次,根据目标在动态背景下的位置和位移,确定与目标匹配较好的检测范围,得到检测范围内正确匹配点的最小包围矩形,然后更新目标模板;该算法避免了对目标与背景之间复杂相对运动的分析,减少了不匹配点和计算量。该算法可以快速准确地跟踪无遮挡的目标,在小遮挡情况下具有较强的鲁棒性。
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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