Comparing Effectiveness of Feature Detectors in Obstacles Detection from a Video
- https://doi.org/10.2991/jrnal.2014.1.3.3How to use a DOI?
- Feature detectors, Harris, SIFT, SURF, FAST, car vision
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.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Shaohua Qian AU - Joo Kooi Tan AU - Hyoungseop Kim AU - Seiji Ishikawa AU - Takashi Morie AU - Takashi Shinomiya PY - 2014 DA - 2014/12/15 TI - Comparing Effectiveness of Feature Detectors in Obstacles Detection from a Video JO - Journal of Robotics, Networking and Artificial Life SP - 184 EP - 188 VL - 1 IS - 3 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2014.1.3.3 DO - https://doi.org/10.2991/jrnal.2014.1.3.3 ID - Qian2014 ER -