Single view reconstruction of transparent, mirror and diffuse surfaces
HKU Theses Online (HKUTO)(2018)
摘要
3D reconstruction has been a fundamental problem in computer vision and has many applications. However, existing methods are mostly designed for diffuse surfaces under multiple viewpoints. This thesis tackles three reconstruction problems under a single view, namely, transparent object reconstruction, mirror surface reconstruction, and diffuse surface reconstruction. Besides, semantic correspondence, which is essential for not only 3D reconstruction but also image understanding, is also investigated in this thesis. In the first part of this thesis, a novel and practical approach is presented for transparent object reconstruction under a fixed viewpoint. A simple and handy setup is introduced to alter the incident light paths before light rays enter the object, followed by a surface recovery method based on reconstructing and triangulating such incident light paths. Our approach does not need to explicitly model the complex interactions of light as it travels through the object, assuming neither any parametric form for shape of the object nor exact number of refractions and reflections occur when light travels through the object. It can handle a transparent object with a complex structure, with an unknown and even inhomogeneous refractive index. This thesis then considers the problem of mirror surface reconstruction under a fixed viewpoint. We first derive an analytical solution to recover the camera projection matrix, and then optimize the camera projection matrix by minimizing reprojection errors with a cross-ratio formulation. The mirror surface is finally reconstructed based on the optimized cross-ratio constraint. The proposed method only needs reflection …
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络