基于SIFT和SURF的立体视觉里程计特征检测和特征匹配性能评价

2014 IEEE REGION 10 SYMPOSIUM Pub Date : 2014-04-14 DOI:10.1109/TENCONSPRING.2014.6863025

Norhayati Mohd. Suaib, M. Marhaban, M. Saripan, S. A. Ahmad

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引用次数: 19

摘要

特征检测和特征匹配是视觉里程测量过程中最关键的部分。为了适应视觉里程计的实时过程，这两个阶段都必须具有鲁棒性，同时还要具有快速的计算速度。提出了尺度不变特征变换(SIFT)和加速鲁棒特征变换(SURF)性能的评价方法。结果表明，SURF在匹配点率和计算时间上都优于SIFT。

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Performance evaluation of feature detection and feature matching for stereo visual odometry using SIFT and SURF

Feature detection and feature matching are the most crucial parts in visual odometry process. In order to suit the real time process in visual odometry, both of the stages must be robust but at the same time are fast to compute. This paper presents the evaluation of Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Feature (SURF) performances. The results show that SURF is outperform than SIFT in term of rate of matched points and also in computational time.

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2014 IEEE REGION 10 SYMPOSIUM

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