Integrating Computer Vision in Construction Estimations and 3D Modelings

Abstract

Computer vision and building information modeling (BIM) have gained significant attention in various fields, including construction, architecture, and infrastructure management. This study presents a novel method for automatically generating 3D models and estimating quantities of construction materials from 2D scanned floor plans using computer vision techniques. The proposed Python-based program integrates complex steps, such as image processing, line and room detection, wall recognition, and 3D model generation using Blender. Additionally, the program accurately calculates the areas of different elements in the floor plan and provides detailed cost estimations for materials like cement, steel, bricks, and tiles for various masonry construction. The results of the program are encouraging, showcasing its potential to be a valuable tool in the future for digital 3D modeling and estimation in construction projects. The program aims to minimize human effort and automate processes, making it user-friendly and efficient for architects, contractors, and clients alike. However, some limitations exist, such as resolution restrictions and sub-structure estimations, which can be addressed in future enhancements.