Texture and Shadow Insensitive Metric for Image-based Reconstruction

被引:0
作者
Wu, Rui [1 ]
Zhao, Xu [1 ]
Zhou, Zhong [1 ]
Wu, Wei [1 ]
机构
[1] Beihang Univ, State Key Lab Virtual Real Technol & Syst, Sch Comp Sci & Engn, Beijing, Peoples R China
来源
2012 IEEE 24TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2012), VOL 1 | 2012年
关键词
IRRADIANCE; RADIANCE;
D O I
10.1109/ICTAI.2012.140
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes an accurate metric for image-based 3d reconstruction without ground truth. Specially, our metric is insensitive to texture changing and shadows, which are commonly occurred in real world scenes. Based on the inter-reflected rendering model, we improve the accuracy of previous irradiance-based metric. Additionally, we estimate the reflectance of each vertex on the surface to support the case with varying reflectance. We also consider the difference between estimated and observed irradiance in our metric to further eliminate the boundary effect of texture changing or self-shadow. Experiments on both indoor and outdoor datasets illustrate the effectiveness of our metric. Our evaluation results are not only more accurate than the results of previous metrics, but also insensitive to the texture and shadow.
引用
收藏
页码:988 / 993
页数:6
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