Intelligent Reading Assistant Using Egocentric Vision and Large Language Model for Visually Impaired Users

แนวคิดหลัก

An intelligent reading assistant system based on smart glasses with embedded RGB cameras and a Large Language Model (LLM) that can process textual information from the user's perspective, understand their preferences, and provide personalized guidance and information.

บทคัดย่อ

The proposed system utilizes Aria smart glasses with embedded RGB cameras to capture egocentric video of the user's surroundings. The video is processed using state-of-the-art object detection and optical character recognition (OCR) techniques to extract textual information, such as from a restaurant menu. The extracted text is then fed into a Large Language Model (LLM), specifically GPT4, to create a digital representation of the menu.

The system also incorporates the user's personal preferences, such as dietary restrictions or food likes/dislikes, which are retrieved from various sources (e.g., bank transactions, Google Photos, Google Maps). The LLM-based chatbot then uses this personalized information to provide contextual and tailored recommendations to the user, such as suggesting suitable menu items.

The system was evaluated in a real-world setting by having four participants, each with a different native language, interact with the system while reading menus from various restaurants. The results showed a high accuracy of 96.77% in text retrieval and all participants rated the system's performance and recommendations as highly satisfactory, with an average rating of 4.87 out of 5.

The proposed framework highlights the potential of integrating egocentric vision, LLMs, and personalized data to create an effective and accessible reading assistance solution for visually impaired individuals, addressing challenges in daily activities and improving their independence and quality of life.

สถิติ

The number of adults aged 50 and over with visual impairment worldwide was estimated to be around 186 million in 2010.
The prevalence of uncorrectable vision problems among adults aged 40 years and older in the United States exceeded 3 million and is projected to increase to 7 million by 2050.

คำพูด

"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."
"Partial vision loss creates challenges in performing Activities of Daily Living (ADLs) and thus increases older adults' dependence on other people's assistance."

ข้อมูลเชิงลึกที่สำคัญจาก

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

by Wiktor Mucha... ที่ arxiv.org 04-16-2024

https://arxiv.org/pdf/2404.09254.pdf

สอบถามเพิ่มเติม

How can the proposed system be further expanded to assist visually impaired individuals in other daily tasks beyond reading, such as navigation or object identification?

The proposed system can be expanded to assist visually impaired individuals in various daily tasks by integrating additional functionalities and technologies. For navigation assistance, the system can incorporate GPS capabilities to provide real-time guidance and location information. This can help users navigate unfamiliar environments with audio cues or haptic feedback. Object identification can be enhanced by integrating computer vision algorithms that can recognize and describe objects in the user's surroundings. This feature can be particularly useful for identifying obstacles, products in a store, or even faces of people. By leveraging machine learning models and sensor fusion techniques, the system can provide a holistic solution for visually impaired individuals to navigate, identify objects, and interact with their environment more effectively.

What are the potential privacy and security concerns associated with the use of personal data in the system, and how can they be addressed to ensure user trust and adoption?

The use of personal data in the system raises significant privacy and security concerns that need to be addressed to ensure user trust and adoption. Some potential concerns include unauthorized access to sensitive information, data breaches, and misuse of personal data for targeted advertising or profiling. To mitigate these risks, the system should implement robust data encryption protocols to secure user data both in transit and at rest. Additionally, strict access controls and authentication mechanisms should be in place to limit data access to authorized personnel only. Transparent data handling policies and user consent mechanisms should be established to inform users about how their data will be used and give them control over their information. Regular security audits and compliance with data protection regulations can also help build trust among users and demonstrate a commitment to safeguarding their privacy.

How can the integration of multimodal sensors, such as depth cameras or audio input, enhance the capabilities of the reading assistance system and provide a more comprehensive solution for visually impaired users?

Integrating multimodal sensors, such as depth cameras or audio input, can significantly enhance the capabilities of the reading assistance system and provide a more comprehensive solution for visually impaired users. Depth cameras can enable the system to perceive the 3D structure of the environment, allowing for better object recognition and spatial awareness. This can help users navigate obstacles more effectively and interact with their surroundings with greater precision. Audio input, combined with natural language processing algorithms, can enable users to interact with the system through voice commands, making the interface more intuitive and accessible. Additionally, audio feedback can provide real-time information about the user's environment, such as reading out text or describing objects. By integrating these multimodal sensors, the system can offer a more immersive and interactive experience for visually impaired users, enhancing their independence and quality of life.