Vision System with 3D Audio Feedback to assist Navigation for Visually Impaired

S, Aakash Krishna G; Pon, Vijay Nirmal; Rai, Saumya; Baskar, A.

doi:10.1016/j.procs.2020.03.216

Cited by 15 publications

(1 citation statement)

References 10 publications

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“…Krishna et al [31] have presented a new "vision system with 3D audio feedback mechanism" to guide the VI people during their navigation. During their movement, the intuitive cognize corresponding to the localization of the object along their path was notified to the blind people via the variation in the intensity of the sounds of earphones.…”

Section: Related Workmentioning

confidence: 99%

A Novel Approach for Object Detection Using Optimized Convolutional Neural Network to Assist Visually Impaired People

Pardeshi¹,

Wagh²,

Kharat³

et al. 2023

Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVA

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Human race is blessed with the five basic senses such as touch, taste, smell, hearing and the most important of them all 'vision or eyesight'. It is very difficult to survive without any one of them. Unfortunately a mass population across the globe suffers from the ill effects of vision, hampering their daily life. Detecting objects and providing navigational instructions in an indoor environment can considerably improve the day-to-day quality of life of visually impaired people. The motive of this research work is to propose a solution approach for assisting visually impaired population by identifying obstacles in front of them considering indoor environment. This approach focuses on feature extraction and object detection using Convolutional Neural Network (CNN) from a real time video. For this a head mounted image acquisition device may be used to detect the objects from the scene ahead and information of the detected objects is provided to the visually impaired (VI) person through the audio modality. As a first step towards the overall conceptual process, an object detection system is presented in this article, which processes the live video stream captured through the acquisition device. The video is processed frame-by-frame, treating each frame as a separate image and then using the proposed feature extraction and object detection algorithm to identify the objects.

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Section: Related Workmentioning

confidence: 99%