Use of Computer Vision to Develop a Device to Assist Visually Impaired People with Social Distance.

Authors

  • Lucas Nadolskis University of Minnesota--Twin Cities

Keywords:

Technology For Blind People, Accessibility For Blind People, Computer Vision., Deep Learning, Machine Learning

Abstract

The project developed a device to assist blind and visually impaired users in complying with social distance rules. The main challenge was how to identify people from other objects and notify the user accordingly. Equally ambiguous was how to best notify the user that a person was violating the social distance rules. The hardware used is a Raspberry Pi running an image classification algorithm and hooked to a depth camera. The use of prediction labels and accuracy combined with the distance calculated by the depth camera made it possible to detect when a person was getting closer than 2 meters (6 ft) to the user. The device was tested both in daylight and at night, and with different lighting conditions. The device responded with a accuracy close to 1.9 meters. which is very acceptable. Testing showed that the camera is capable of identifying people coming from a 30 degrees angle from either side at around 1.9 meters of distance, giving a good range of object detection.

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Published

2021-05-18

How to Cite

Nadolskis, L. (2021). Use of Computer Vision to Develop a Device to Assist Visually Impaired People with Social Distance. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15974-15975. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17983

Issue

Section

AAAI Undergraduate Consortium