Depth Estimation in Multi-View Stereo Based on Image Pyramid

被引:1
|
作者
Xu, Hanfei [1 ]
Cai, Yangang [1 ]
Wang, Ronggang [1 ]
机构
[1] Peking Univ, Shenzhen Grad Sch, Shenzhen, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
3D reconstruction; Multi-View Stereo; image pyramid; SILHOUETTE;
D O I
10.1145/3297156.3297238
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
3D reconstruction using Struct-from-Motion(SFM) and Multi-View Stereo(MVS), along with image-based rendering (IBR), has been applied to the synthesis of the virtual-viewpoint images. We have investigated the latest works, and we find that the underlying 3D reconstruction methods are quite efficient for buildings and regular structure. However, for scenes with weakly textured or discontinuous-depth regions, these methods do not work well. Such regions do not contain reliable or dense 3D information, and as a result, biases will occur in the procedure of synthesizing point clouds. In this paper, we propose a new method using the image pyramid in the depth-map merging based MVS framework. In this method, we use multi-scale image information to estimate depth. Our method can capture more 3D information in weakly textured or discontinuous-depth regions, and finally obtain the better visible effect in the virtual-viewpoint images.
引用
收藏
页码:345 / 349
页数:5
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