Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77672
Title: 3D surface detail enhancement from a single normal map
Authors: Xie, W 
Wang, M
Qi, X 
Zhang, L 
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: Proceedings of the IEEE International Conference on Computer Vision, 2017, 22-29 Oct. 2017, 8237517, p. 2344-2352 How to cite?
Abstract: In 3D reconstruction, the obtained surface details are mainly limited to the visual sensor due to sampling and quantization in the digitalization process. How to get a fine-grained 3D surface with low-cost is still a challenging obstacle in terms of experience, equipment and easyto-obtain. This work introduces a novel framework for enhancing surfaces reconstructed from normal map, where the assumptions on hardware (e.g., photometric stereo setup) and reflection model (e.g., Lambertion reflection) are not necessarily needed. We propose to use a new measure, angle profile, to infer the hidden micro-structure from existing surfaces. In addition, the inferred results are further improved in the domain of discrete geometry processing (DGP) which is able to achieve a stable surface structure under a selectable enhancement setting. Extensive simulation results show that the proposed method obtains significantly improvements over uniform sharpening method in terms of both subjective visual assessment and objective quality metric.
URI: http://hdl.handle.net/10397/77672
ISBN: 9.78154E+12
DOI: 10.1109/ICCV.2017.255
Appears in Collections:Conference Paper

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