Fast Approximated SIFT Applied in Moving Objects Detection

Wei Tang, Zhaoshun Wang
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引用次数: 1

Abstract

To make the moving object detection faster and more reliable, in this paper we present a novel method based on fast approximated SIFT descriptor. The main idea is to compute the feature descriptor of a key-point using the integral histogram of the surrounding squared region. The feature descriptor could be further used in the feature matching between two sequential frames in the image sequence. When involved in calculating hundreds of feature descriptors, this method is profitable as it reduced computational cost, accelerated the computational speed while still maintained a fairly stable matching performance compared with the traditional SIFT descriptor. The experimental results showed that it was nearly three times faster than before and was able to meet more restrict real-time requirements.
快速近似SIFT在运动目标检测中的应用
为了使运动目标检测更快、更可靠,本文提出了一种基于快速近似SIFT描述子的运动目标检测方法。主要思想是利用周围平方区域的积分直方图计算关键点的特征描述符。该特征描述符可进一步用于图像序列中两个连续帧之间的特征匹配。当涉及到数百个特征描述子的计算时,与传统的SIFT描述子相比,该方法降低了计算成本,加快了计算速度,同时保持了相当稳定的匹配性能。实验结果表明,该方法的速度比以前快了近3倍,能够满足更严格的实时性要求。
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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