Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance

• URL: http://arxiv.org/abs/2105.11599v1
• Date: Tue, 25 May 2021 01:28:54 GMT
• Title: Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance
• Authors: Ziang Cheng, Hongdong Li, Yuta Asano, Yinqiang Zheng, Imari Sato
• Abstract summary: Multi-view reconstruction of texture-less objects with unknown surface reflectance is a challenging task. This paper proposes a simple and robust solution to this problem based on a co-light scanner.
• Score: 86.05191217004415
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Recovering the 3D geometry of a purely texture-less object with generally unknown surface reflectance (e.g. non-Lambertian) is regarded as a challenging task in multi-view reconstruction. The major obstacle revolves around establishing cross-view correspondences where photometric constancy is violated. This paper proposes a simple and practical solution to overcome this challenge based on a co-located camera-light scanner device. Unlike existing solutions, we do not explicitly solve for correspondence. Instead, we argue the problem is generally well-posed by multi-view geometrical and photometric constraints, and can be solved from a small number of input views. We formulate the reconstruction task as a joint energy minimization over the surface geometry and reflectance. Despite this energy is highly non-convex, we develop an optimization algorithm that robustly recovers globally optimal shape and reflectance even from a random initialization. Extensive experiments on both simulated and real data have validated our method, and possible future extensions are discussed.

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