3D Surface Detail Enhancement from a Single Normal Map

Wuyuan Xie, Miaohui Wang, Xianbiao Qi, Lei Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2344-2352
Number of pages9
ISBN (Electronic)9781538610329
DOIs
Publication statusPublished - 22 Dec 2017
Event16th IEEE International Conference on Computer Vision, ICCV 2017 - Venice Convention Center, Venice, Italy
Duration: 22 Oct 201729 Oct 2017

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
Volume2017-October
ISSN (Print)1550-5499

Conference

Conference16th IEEE International Conference on Computer Vision, ICCV 2017
CountryItaly
CityVenice
Period22/10/1729/10/17

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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