Binocular Stereoscopic Vision Algorithm Based on Improved SIFT Feature

DOI

10.2991/emim-17.2017.230How to use a DOI?

Keywords

The improved SIFT algorithm; Binocular stereo; Object location; Feature matching

Abstract

Stereo matching is the most important step in binocular vision, the traditional regional stereo matching to obtain the target three-dimensional information is slow and inaccurate. This paper presents an improved SIFT algorithm. Firstly, making the epipolar constraint on the left and right image; secondly, selecting the ROI of target from the left of binocular images, and reducing running time by reducing the dimension of feature vectors and accelerating the matching speed by using BBF algorithm based on KD tree; finally, removing the false matching by using RANSAC algorithm. The improved SIFT algorithm can get the target's feature points quickly and accurately, so the 3D coordinates can be calculated by the triangulation method speedy.

Copyright

© 2017, 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/).

Download article (PDF)

TY  - CONF
AU  - Jian Liu
AU  - Yao Lu
PY  - 2017/04
DA  - 2017/04
TI  - Binocular Stereoscopic Vision Algorithm Based on Improved SIFT Feature
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 1139
EP  - 1143
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.230
DO  - 10.2991/emim-17.2017.230
ID  - Liu2017/04
ER  -