[1]冯春,吴小锋,尹飞鸿,等. 基于局部特征匹配的双焦单目立体视觉深度估计[J].计算机技术与发展,2016,26(10):55-59.
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 基于局部特征匹配的双焦单目立体视觉深度估计()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年10期
页码:
55-59
栏目:
智能、算法、系统工程
出版日期:
2016-10-10

文章信息/Info

Title:
 Depth Estimation for Bifocal Monocular Stereo Vision Based on Local Image Feature Descriptors Matching
文章编号:
1673-629X（2016)10-0050-05
作者:
 冯春; 吴小锋; 尹飞鸿; 杨名利
 常州工学院 机械与车辆工程学院
Author(s):
 FENG Chun; WU Xiao-feng; YIN Fei-hong; YANG Ming-li
关键词:
 ; 双焦成像; 图像匹配; 局部特征; 深度估计; SSURF
Keywords:
 ; bifocal imaging; image matching; local feature; depth estimation; SSURF
分类号:
TP391
文献标志码:
A
摘要:
 针对基于双焦单目立体视觉的图像焦距变化和相似图像误匹配率高的问题,提出利用局部特征描述子结合“两步匹配法”进行图像匹配。将局部特征描述子引入基于双焦单目立体视觉系统中进行图像匹配。提出“两步匹配法”获取特征点集合,即交换小焦距与大焦距图像匹配顺序获取两个特征点集合,求交运算得到新的集合,并计算深度值。实验结果表明,SSURF( Simplified Speed-Up Robust Feature)匹配速度最快,获取的深度值与理想的深度值误差较小,从而验证了将局部特征用于双焦单目立体视觉进行图像匹配从而完成深度估计是可行的。
Abstract:
 Focused on the issue of the focal length change of image based on the bifocal monocular stereo vision and the high rate of false matching of similar image,the use of local feature descriptors and‘Two-step Matching Method’ for image matching is proposed. Local feature descriptors are used to complete the image feature matching in the monocular stereo vision system and compared with each other.‘Two-step matching method’ is used to obtain the set of feature points,and two sets of feature points are obtained by changing the order of two images,the small focal length one and the large focal length one,and then a new set can be got by an intersection operation be-tween the above two point sets,thereby the depth estimation computation could be completed by the new set. Experimental results show that the SSURF has the fastest matching rate,and the depth value obtained by the above method is approximately equivalent to the ideal depth value,so it verifies that the local feature descriptors used for image matching based on bifocal monocular stereo vision to compute the depth estimation is feasible.

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更新日期/Last Update: 2016-11-25