Iterative Low-Poly Building Model Reconstruction from Mesh Soups Based on Contour

Author:

Xiao Xiao1,Liu Yuhang2,Zhang Yanci1

Affiliation:

1. College of Computer Science, Sichuan University, Chengdu 610065, China

2. National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, Chengdu 610065, China

Abstract

Existing contour-based building-reconstruction methods face the challenge of producing low-poly results. In this study, we introduce a novel iterative contour-based method to reconstruct low-poly meshes with only essential details from mesh soups. Our method focuses on two primary targets that determine the quality of the results: reduce the total number of contours, and generate compact surfaces between contours. Specifically, we implemented an iterative pipeline to gradually extract vital contours by loss and topological variance, and potential redundant contours will be removed in a post-processing procedure. Based on these vital contours, we extracted the planar primitives of buildings as references for contour refinement to obtain compact contours. The connection relationships between these contours are recovered for surface generation by a contour graph, which is constructed using multiple bipartite graphs. Then, a low-poly mesh can be generated from the contour graph using our contour-interpolation algorithm based on polyline splitting. The experiments demonstrated that our method produced satisfactory results and outperformed the previous methods.

Funder

National Key Project of China

Sichuan Science and Technology Program

Publisher

MDPI AG

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