Authors
Shaohua Qian, Joo Kooi Tan, Hyoungseop Kim, Seiji Ishikawa, Takashi Morie, Takashi Shinomiya
Corresponding Author
Shaohua Qian
Available Online 15 December 2014.
DOI
https://doi.org/10.2991/jrnal.2014.1.3.3How to use a DOI?
Keywords
Feature detectors, Harris, SIFT, SURF, FAST, car vision
Abstract
We have already proposed an obstacles detection method using a video taken by a vehicle-mounted monocular camera. In this method, correct obstacles detection depends on whether we can accurately detect and match feature points. In order to improve the accuracy of obstacles detection, in this paper, we make comparison among four most commonly used feature detectors; Harris, SIFT, SURF and FAST detectors. The experiments are done using our obstacles detection method. The experimental results are compared and discussed, and then we find the most suitable feature point detector for our obstacles detection method.

Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).