A Kaleidoscopic Approach to Surround Geometry and Reflectance Acquisition
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
Paper [final version] (~13MB)
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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.