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A Kaleidoscopic Approach to Surround Geometry and Reflectance Acquisition


kaleidoscopic reconstruction

Abstract

We describe a system for acquiring reflectance fields of objects without moving parts and without a massively parallel hardware setup. Our system consists of a set of planar mirrors which serve to multiply a single camera and a single projector into a multitude of virtual counterparts. Using this arrangement, we can acquire reflectance fields with an average angular sampling rate of about 120+ view/light pairs per surface point. The mirror system allows for freely programmable illumination with full directional coverage. We employ this setup to realize a 3D acquisition system that employs structured illumination to capture the unknown object geometry, in addition to dense reflectance sampling. On the software side, we combine state-of-the-art 3D reconstruction algorithms with a reflectance sharing technique based on non-negative matrix factorization in order to reconstruct a joint model of geometry and reflectance. We demonstrate for a number of test scenes that the kaleidoscopic approach can acquire complex reflectance properties faithfully. The main limitation is that the multiplexing approach limits the attainable spatial resolution, trading it off for improved directional coverage.

Keywords: kaleidoscope, reconstruction, geometry, point cloud

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Bibliography

I. Ihrke, I. Reshetouski, A. Manakov, A. Tevs, M. Wand, H.-P. Seidel "A Kaleidoscopic Approach to Surround Geometry and Reflectance Acquisition" , CVPR Workshop on Computational Cameras and Displays (CCD), 2012.