arXiv:2412.19954cs.CVcs.AI2024-12被引 6

用视觉问答系统实时评估建筑工人姿势风险,准确率达96.5%。

ErgoChat: a Visual Query System for the Ergonomic Risk Assessment of Construction Workers

  • 基于视觉语言模型实现工人姿势风险的交互式问答与描述生成
  • 视觉问答准确率96.5%,图像描述质量优于通用数据训练模型
  • 专为建筑安全设计的数据集,适合工地健康监测场景

建筑行业工人长期处于高强度体力劳动和工具使用状态,易引发与姿势相关的职业伤害,是长期存在的健康隐患。传统人体工学风险评估(ERA)缺乏交互反馈能力。尽管视觉语言模型(VLMs)可基于图像回答姿势风险问题或生成描述,但尚未被广泛应用。本文提出一个面向建筑工人姿势风险评估的交互式视觉查询系统,支持视觉问答(VQA)和图像描述(IC)功能。系统还构建了专用数据集用于训练与测试。实验表明,VQA准确率达到96.5%;九项指标评估及专家打分显示,该方法在图像描述任务上优于仅在通用数据上训练的同架构模型。本研究为生成式AI在交互式人体工学评估中的应用开辟新方向。

原文摘要 · Abstract (English)

In the construction sector, workers often endure prolonged periods of high-intensity physical work and prolonged use of tools, resulting in injuries and illnesses primarily linked to postural ergonomic risks, a longstanding predominant health concern. To mitigate these risks, researchers have applied various technological methods to identify the ergonomic risks that construction workers face. However, traditional ergonomic risk assessment (ERA) techniques do not offer interactive feedback. The rapidly developing vision-language models (VLMs), capable of generating textual descriptions or answering questions about ergonomic risks based on image inputs, have not yet received widespread attention. This research introduces an interactive visual query system tailored to assess the postural ergonomic risks of construction workers. The system's capabilities include visual question answering (VQA), which responds to visual queries regarding workers' exposure to postural ergonomic risks, and image captioning (IC), which generates textual descriptions of these risks from images. Additionally, this study proposes a dataset designed for training and testing such methodologies. Systematic testing indicates that the VQA functionality delivers an accuracy of 96.5%. Moreover, evaluations using nine metrics for IC and assessments from human experts indicate that the proposed approach surpasses the performance of a method using the same architecture trained solely on generic datasets. This study sets a new direction for future developments in interactive ERA using generative artificial intelligence (AI) technologies.

人体工学视觉问答建筑安全AI评估

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