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

DOI

10.2991/978-94-6463-196-8_17How to use a DOI?

Keywords

Vision; Convolutional Neural Network (CNN); Visually Impaired (VI); Feature Extraction; Object Detection; Audio Modality

Abstract

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.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Suraj Pardeshi
AU  - Nikhil Wagh
AU  - Kailash Kharat
AU  - Vikul Pawar
AU  - Pravin Yannawar
PY  - 2023
DA  - 2023/08/10
TI  - A Novel Approach for Object Detection Using Optimized Convolutional Neural Network to Assist Visually Impaired People
BT  - Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
PB  - Atlantis Press
SP  - 187
EP  - 207
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-196-8_17
DO  - 10.2991/978-94-6463-196-8_17
ID  - Pardeshi2023
ER  -