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Image-Based Structural Analysis Using Computer Vision and LLMs: PhotoBeamSolver

Altamirano-Muñiz Emilio Fernando

Abstract

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.

Image-Based Structural Analysis Using Computer Vision and LLMs: PhotoBeamSolver

Abstract

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.
Paper Structure (5 sections, 7 figures, 1 table)

This paper contains 5 sections, 7 figures, 1 table.

Table of Contents

  1. Introduction
  2. Formulation
  3. Discussion
  4. Results
  5. Conclusions

Figures (7)

  • Figure 1: On the left, structural component recognition is applied on a bridge DBLP:journals/corr/abs-1806-06820. In the center, the detection of an excavator arm is performed doi:10.1061/(ASCE)CP.1943-5487.0001060. On the right, detection of workers and machinery in situ.rempro
  • Figure 2: Object detection applied to supports of a theoretical beam (left) and an example of PhotoBeamSolver using YOLOv5.(right)
  • Figure 3: Examples of training datasets
  • Figure 4: Flow chart of PhotoBeamSolver
  • Figure 5: Conceptualization of a computer vision based structural analysis.
  • ...and 2 more figures