Authors: Ahmet Bahaddin Ersoz
Abstract: The integration of Large Vision-Language Models (LVLMs) such as OpenAI’s
GPT-4 Vision into various sectors has marked a significant evolution in the
field of artificial intelligence, particularly in the analysis and
interpretation of visual data. This paper explores the practical application of
GPT-4 Vision in the construction industry, focusing on its capabilities in
monitoring and tracking the progress of construction projects. Utilizing
high-resolution aerial imagery of construction sites, the study examines how
GPT-4 Vision performs detailed scene analysis and tracks developmental changes
over time. The findings demonstrate that while GPT-4 Vision is proficient in
identifying construction stages, materials, and machinery, it faces challenges
with precise object localization and segmentation. Despite these limitations,
the potential for future advancements in this technology is considerable. This
research not only highlights the current state and opportunities of using LVLMs
in construction but also discusses future directions for enhancing the model’s
utility through domain-specific training and integration with other computer
vision techniques and digital twins.
Source: http://arxiv.org/abs/2412.16108v1
