Seuillage par hyst\'er\'esis pour le test de photo-consistance des voxels dans le cadre de la reconstruction 3D

TL;DR

This paper introduces an automated hysteresis thresholding method for voxel photo-consistency testing in 3D reconstruction, enhancing accuracy and smoothness without preset thresholds by using spatial coherence and fuzzy membership.

Contribution

It proposes a fully automated, adaptive hysteresis thresholding approach that incorporates spatial coherence and fuzzy logic to improve voxel classification in 3D reconstruction.

Findings

Preliminary results show improved reconstruction quality.

Method automatically adapts thresholds based on image projections.

Enhanced smoothness and precision in 3D models.

Abstract

Voxel coloring is a popular method of reconstructing a three-dimensional surface model from a set of calibrated 2D images. However, the reconstruction quality is largely dependent on a thresholding procedure allowing the authors to decide, for each voxel, whether it is photo-consistent or not. Even so, this method is widely used because of its simplicity and low computational cost. We have returned to this method in order to propose an improvement in the thresholding step which will be fully automated. Indeed, the geometrical information is implicitly integrated using an hysteresis thresholding which takes into account the spatial coherence of color voxels. Moreover, the ambiguity of choosing the thresholds is extremely minimized by defining a fuzzy degree of membership of each voxel into the class of consistent voxels. Also, there is no need for preset thresholds since the hysteresis ones are defined automatically and adaptively depending on the number of images that the voxel isprojected onto. Preliminary results are very promising and demonstrate that the proposed method performs automatically precise and smooth volumetric scene reconstruction.