Thermal Polarimetric Multi-View Stereo
Takahiro Kushida, Kenichiro Tanaka
摘要
This paper introduces a novel method for detailed 3D shape reconstruction utilizing thermal polarization cues. Unlike state-of-the-art methods, the proposed approach is independent of illumination and material properties. In this paper, we formulate a general theory of polarization observation and show that long-wave infrared (LWIR) polarimetric imaging is free from the ambiguities that affect visible polarization analyses. Subsequently, we propose a method for recovering detailed 3D shapes using multi-view thermal polarimetric images. Experimental results demonstrate that our approach effectively reconstructs fine details in transparent, translucent, and heterogeneous objects, outperforming existing techniques.
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- Multiview Neural Surface Reconstruction by Disentangling Geometry and AppearanceLior Yariv, Yoni Kasten, Dror Moran, Meirav Galun 等NeurIPS 2020 · 被引用 1,010 次
- Implicit Geometric Regularization for Learning ShapesAmos Gropp, Lior Yariv, Niv Haim, Matan Atzmon 等ICML 2020 · 被引用 1,001 次
- Shape from Polarization for Complex Scenes in the WildChenyang Lei, Chenyang Qi, Jiaxin Xie, Na Fan 等CVPR 2022 · 被引用 60 次
- Sparse ellipsometry: portable acquisition of polarimetric SVBRDF and shape with unstructured flash photographyInseung Hwang, Daniel S. Jeon, Adolfo Muñoz, Diego Gutierrez 等SIGGRAPH 2022 · 被引用 34 次
- Shape from Thermal Radiation: Passive Ranging Using Multi-spectral LWIR MeasurementsYasuto Nagase, Takahiro Kushida, Kenichiro Tanaka, Takuya Funatomi 等CVPR 2022 · 被引用 12 次
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