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.2014.1.3.3
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/).