Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

Binocular Stereoscopic Vision Algorithm Based on Improved SIFT Feature

Authors
Jian Liu, Yao Lu
Corresponding Author
Jian Liu
Available Online April 2017.
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/).

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Volume Title
Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
Series
Advances in Computer Science Research
Publication Date
April 2017
ISBN
978-94-6252-356-2
ISSN
2352-538X
DOI
10.2991/emim-17.2017.230How to use a DOI?
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/).

Cite this article

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  -