Multi-view Non-rigid Refinement and Normal Selection for High Quality 3D Reconstruction

Haque, Sk Mohammadul and Govindu, Venu Madhav (2017) Multi-view Non-rigid Refinement and Normal Selection for High Quality 3D Reconstruction. In: 16th IEEE International Conference on Computer Vision, ICCV 2017, 22 - 29 October 2017, Venice, pp. 2401-2409.

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Abstract

In recent years, there have been a variety of proposals for high quality 3D reconstruction by fusion of depth and normal maps that contain good low and high frequency information respectively. Typically, these methods create an initial mesh representation of the complete object or scene being scanned. Subsequently, normal estimates are assigned to each mesh vertex and a mesh-normal fusion step is carried out. In this paper, we present a complete pipeline for such depth-normal fusion. The key innovations in our pipeline are twofold. Firstly, we introduce a global multi-view non-rigid refinement step that corrects for the non-rigid misalignment present in the depth and normal maps. We demonstrate that such a correction is crucial for preserving fine-scale 3D features in the final reconstruction. Secondly, despite adequate care, the averaging of multiple normals invariably results in blurring of 3D detail. To mitigate this problem, we propose an approach that selects one out of many available normals. Our global cost for normal selection incorporates a variety of desirable properties and can be efficiently solved using graph cuts. We demonstrate the efficacy of our approach in generating high quality 3D reconstructions of both synthetic and real 3D models and compare with existing methods in the literature.

Item Type:	Conference Paper
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to the Institute of Electrical and Electronics Engineers Inc.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	07 Jun 2022 05:29
Last Modified:	07 Jun 2022 05:29
URI:	https://eprints.iisc.ac.in/id/eprint/73215

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