Guidance scheme for object detection visual impairment assistance equipment

Xiaoya Fang; Shuangshuang Ma; Han Yu; Yuting Shi; Fan Long; Qianyi Liu; Cang Deng; Zhichao Wei; Yuan Wang

doi:10.1117/12.3029625

21 June 2024 Guidance scheme for object detection visual impairment assistance equipment

Xiaoya Fang, Shuangshuang Ma, Han Yu, Yuting Shi, Fan Long, Qianyi Liu, Cang Deng, Zhichao Wei, Yuan Wang

Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 1316735 (2024) https://doi.org/10.1117/12.3029625
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China

Abstract

Patients with visual impairments often face challenges in identifying and navigating environmental obstacles in their daily lives, therefore reliable assistive technologies are needed to improve their quality of life and independence. This study proposes a visual obstacle assistive device guidance scheme that comprehensively utilizes sensor technology and object detection algorithms, aiming to provide comprehensive solutions for patients. We have adopted advanced sensor technology, including cameras, LiDAR and other sensors, to monitor the surrounding environment in real-time. These sensors can detect the distance, shape, and position information of obstacles and transmit this data to the navigation system. We use the YOLOv5 object detection model, which can accurately identify and track various obstacles, including pedestrians, vehicles, etc., under real-time camera input. The output of the target detection model is fused with sensor data to form a comprehensive environmental perception system. The experimental results indicate that the auxiliary device guidance scheme exhibits high accuracy and real-time performance under different environmental conditions, and has a positive impact on improving patients' quality of life and autonomy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaoya Fang, Shuangshuang Ma, Han Yu, Yuting Shi, Fan Long, Qianyi Liu, Cang Deng, Zhichao Wei, and Yuan Wang "Guidance scheme for object detection visual impairment assistance equipment", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 1316735 (21 June 2024); https://doi.org/10.1117/12.3029625

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KEYWORDS

Object detection

Visualization

Cameras

Environmental sensing

Detection and tracking algorithms

Sensors

Data modeling

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