StructuredMesh: 3-D Structured Optimization of Façade Components on Photogrammetric Mesh Models Using Binary Integer Programming

Abstract

The absence of detailed façade elements in photogrammetric building mesh models falls short for complex applications. These models often present irregular surfaces, significant geometric noise, and subpar texture quality, complicating façade parsing. To mitigate these challenges, we introduce StructuredMesh, an innovative approach to augment façade details while adhering to architectural regularity. Our method captures multiview color and depth images with a virtual camera and implements an object detection pipeline to semiautomatically delineate façade elements—such as windows, doors, and balconies—from color images. These elements are mapped into 3-D space using depth information, forming a preliminary façade layout. By harnessing architectural intelligence, we engage binary integer programming (BIP) for 3-D layout optimization, targeting component positions, orientations, and sizes. The resulting refined layout underpins the façade reconstruction of the mesh model through instance replacement. Our method’s efficacy was confirmed on three distinct datasets. Employing the 3-D layout evaluation metrics we proposed, StructuredMesh surpasses conventional methods in numerical precision and regularity enhancement.