TEXT2TASTE: A Versatile Egocentric Vision System for Intelligent Reading Assistance Using Large Language Model

TL;DR

TEXT2TASTE introduces a smart glasses system utilizing egocentric vision and large language models to assist visually impaired users in reading, understanding, and querying text in real-world scenarios, enhancing independence and safety.

Contribution

The paper presents a novel egocentric vision system with integrated LLMs for intelligent reading assistance, extending beyond traditional corrective lenses to include text localization, retrieval, and summarization.

Findings

High accuracy in text localization and retrieval.

Effective real-world application demonstrated with user satisfaction.

System provides accurate and helpful meal suggestions.

Abstract

The ability to read, understand and find important information from written text is a critical skill in our daily lives for our independence, comfort and safety. However, a significant part of our society is affected by partial vision impairment, which leads to discomfort and dependency in daily activities. To address the limitations of this part of society, we propose an intelligent reading assistant based on smart glasses with embedded RGB cameras and a Large Language Model (LLM), whose functionality goes beyond corrective lenses. The video recorded from the egocentric perspective of a person wearing the glasses is processed to localise text information using object detection and optical character recognition methods. The LLM processes the data and allows the user to interact with the text and responds to a given query, thus extending the functionality of corrective lenses with the ability to find and summarize knowledge from the text. To evaluate our method, we create a chat-based application that allows the user to interact with the system. The evaluation is conducted in a real-world setting, such as reading menus in a restaurant, and involves four participants. The results show robust accuracy in text retrieval. The system not only provides accurate meal suggestions but also achieves high user satisfaction, highlighting the potential of smart glasses and LLMs in assisting people with special needs.