arXiv:2511.06080cs.CVcs.CY2025-11被引 1

AIDEN用触觉引导帮助视障者更自主地识别物体和导航。

AIDEN: Design and Pilot Study of an AI Assistant for the Visually Impaired

  • 融合YOLO与LLaVA,实现实时物体检测与场景描述。
  • 触觉反馈系统实现实时物体定位,用户满意度高。
  • 适合希望减少听觉负担、提升独立性的视障人士使用。

本文提出AIDEN,一种基于人工智能的辅助系统,旨在提升视障人士的自主性与日常生活质量。视障者常面临物体识别、文字阅读及陌生环境导航难题。现有方案如屏幕阅读器或语音助手虽可获取信息,但易导致听觉过载,并在开放环境中引发隐私担忧。AIDEN采用混合架构,结合YOLO实现实时物体检测,利用大语言视觉助手LLaVA完成场景描述与光学字符识别(OCR)。系统创新性地引入基于盖革计数器隐喻的持续触觉引导机制,实现物体中心对齐且不占用听觉通道,同时通过不存储个人数据保障隐私。通过科技接受模型(TAM)对视障参与者进行评估,结果表明用户对系统易用性和接受度评价较高,尤其认可其直观性与自主性提升。此外,“寻找物体”任务表现出良好实时性能。研究证实,多模态触觉-视觉反馈相比传统音频主导方法,显著提升日常可用性与独立性,为更大规模临床验证提供了有力支持。

原文摘要 · Abstract (English)

This paper presents AIDEN, an artificial intelligence-based assistant designed to enhance the autonomy and daily quality of life of visually impaired individuals, who often struggle with object identification, text reading, and navigation in unfamiliar environments. Existing solutions such as screen readers or audio-based assistants facilitate access to information but frequently lead to auditory overload and raise privacy concerns in open environments. AIDEN addresses these limitations with a hybrid architecture that integrates You Only Look Once (YOLO) for real-time object detection and a Large Language and Vision Assistant (LLaVA) for scene description and Optical Character Recognition (OCR). A key novelty of the system is a continuous haptic guidance mechanism based on a Geiger-counter metaphor, which supports object centering without occupying the auditory channel, while privacy is preserved by ensuring that no personal data are stored. Empirical evaluations with visually impaired participants assessed perceived ease of use and acceptance using the Technology Acceptance Model (TAM). Results indicate high user satisfaction, particularly regarding intuitiveness and perceived autonomy. Moreover, the ``Find an Object'' achieved effective real-time performance. These findings provide promising evidence that multimodal haptic-visual feedback can improve daily usability and independence compared to traditional audio-centric methods, motivating larger-scale clinical validations.

AI辅助触觉反馈视障技术

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