| Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
|---|---|---|
| Article Number | 03053 | |
| Number of page(s) | 5 | |
| Section | Digital Signal and Image Processing | |
| DOI | https://doi.org/10.1051/matecconf/201817303053 | |
| Published online | 19 June 2018 | |
A Survey of Learning Approaches and Application for 3D Vision
Computer Science and Technology, Department of CSSE, Xi’an Jiaotong – Liverpool University, China
Three-dimensional (3D) vision extracted from the stereo images or reconstructed from the two-dimensional (2D) images is the most effective topic in computer vision and video surveillance. Three-dimensional scene is constructed through two stereo images which existing disparity map by Stereo vision. Many methods of Stereo matching which contains median filtering, mean-shift segmentation, guided filter and joint trilateral filters [1] are used in many algorithms to construct the precise disparity map. These methods committed to figure out the image synthesis range in different Stereo matching fields and among these techniques cannot perform perfectly every turn. The paper focuses on 3D vision, introduce the background and process of 3D vision, reviews several classical datasets in the field of 3D vision, based on which the learning approaches and several types of applications of 3D vision were evaluated and analyzed.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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