Image-Based Structural Analysis Using Computer Vision and LLMs: PhotoBeamSolver
This addresses the need for automated structural analysis from drawings in civil engineering, but it appears incremental as it builds on existing computer vision techniques for a specific domain.
The paper tackled the problem of solving idealized beam models from hand-drawn images by developing PhotoBeamSolver, a program using computer vision and statistical learning, and analyzed challenges in integrating computer vision into structural analysis for civil engineering.
This paper presents the development of a documented program capable of solving idealized beam models, such as those commonly used in textbooks and academic exercises, from drawings made by a person. The system is based on computer vision and statistical learning techniques for the detection and visual interpretation of structural elements. Likewise, the main challenges and limitations associated with the integration of computer vision into structural analysis are analyzed, as well as the requirements necessary for its reliable application in the field of civil engineering. In this context, the implementation of the PhotoBeamSolver program is explored, and the current state of computer vision in civil engineering is discussed, particularly in relation to structural analysis, infrastructure inspection, and engineering decision-support systems.