结合SFS和双目模型的单幅图像深度估计算法

计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 161-164.

结合SFS和双目模型的单幅图像深度估计算法

赵子阳, 蒋慕蓉, 黄亚群, 郝健宇, 曾科

云南大学信息学院昆明650500

出版日期:2019-06-14 发布日期:2019-07-02
通讯作者: 蒋慕蓉(1963-),女,教授,主要研究方向为图像处理的数学方法及其智能计算,E-mail:jiangmr@ynu.edu.cn
作者简介:赵子阳(1993-),男,硕士,主要研究方向为图像识别与重建;黄亚群(1971-),女,副教授,主要研究方向为图像处理及智能计算;郝健宇(1992-),男,硕士生,主要研究方向为图像重建;曾科(1992-),男,硕士生,主要研究方向为图像识别。
基金资助:
本文受国家自然科学基金项目(11161055)资助。

Single Image Depth Estimation Algorithm Based on SFS and Binocular Model

ZHAO Zi-yang, JIANG Mu-rong, HUANG Ya-qun, HAO Jian-yu, ZENG Ke

School of Information Science and Engineering,Yunnan University,Kunming 650500,China

Online:2019-06-14 Published:2019-07-02

摘要/Abstract

摘要： 从二维图像中获取图像深度信息是计算机视觉领域的热点问题。经典的双目视觉方法需要相机内部参数和同一场景的多张图像,视觉参数不足容易导致计算错误,而单幅图像只能依靠自身的几何信息得到图像深度。文中针对未知相机参数得到的单幅普通二维图像,结合SFS(从阴影恢复形状)方法,运用图像明暗的几何信息和双目视觉模型获取图像目标深度值,再利用目标轮廓信息对不同目标区域进行赋值,得到图像不同目标距离观察者的远近关系。实验结果表明,所提方法得到的图像深度能较为准确地反映出场景的真实信息,较符合实际观测结果。

关键词: 从阴影恢复形状, 单幅图片, 双目视觉, 图像深度

Abstract: Obtaining depth information from 2D images is a hot topic in the field of computer vision.Classical binocular vision methods require camera parameters and multiple images of the same scene.Insufficient visual parameters can easily lead to errors in calculation,while a single image can only rely on its own geometric information to get the image depth.This paper used the geometric information of the image and the binocular vision model to get the depth value of the object in a single ordinary two-dimensional image with unknown camera parameters.The experimental results show that the image depth obtained by the proposed method can relatively accurately reflect the real information of the scene,which is consistent with the actual observation results.

Key words: Binocular vision, Image depth, SFS, Single-picture

中图分类号:

TP391

赵子阳, 蒋慕蓉, 黄亚群, 郝健宇, 曾科. 结合SFS和双目模型的单幅图像深度估计算法[J]. 计算机科学, 2019, 46(6A): 161-164. https://doi.org/

ZHAO Zi-yang, JIANG Mu-rong, HUANG Ya-qun, HAO Jian-yu, ZENG Ke. Single Image Depth Estimation Algorithm Based on SFS and Binocular Model[J]. Computer Science, 2019, 46(6A): 161-164. https://doi.org/

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