Machine Learning Based Computer Vision Application for Visually Disabled People

Authors

  • Shubhada Mone  Faculty at Department of Computer Engineering, SPPU, India
  • Nihar Salunke   Department of Computer Engineering, SPPU, India
  • Omkar Jadhav  
  • Arjun Barge  
  • Nikhil Magar  

DOI:

https://doi.org//10.32628/CSEIT2173130

Keywords:

Machine Learning, Computer Vision, Mobile Application Development, Cloud Computing

Abstract

With the easy availability of technology, smartphones are playing an important role in every person’s life. Also, with the advancements in computer vision based research, Automatic Driving cars, Object Recognition, Depth Map Prediction, Object Distance Estimation, have reached commendable levels of intelligence and accuracy. Combining the research and technological advancements, we can be hopeful in creating a computer vision based mobile-application which will help guide visually disabled people in performing their day to day tasks with easily available mobile applications. With our study, the visually disabled can perform simple tasks like outdoor/indoor navigation without encountering obstacles, also they can avoid accidental collisions with objects in their surroundings. Currently, there are very few applications which provide the same assistance to the visually impaired. Using physical tools like sticks is a very common practice when it comes to avoiding obstacles in a visually disabled person’s path. Our study will be focused on object detection and depth estimation techniques- two of the most popular and advanced fields in Intelligent Computer vision studies. We have explored more on the traditional challenges and future hopes of incorporating these techniques on embedded devices.

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Published

2021-06-30

Issue

Section

Research Articles

How to Cite

[1]
Shubhada Mone, Nihar Salunke , Omkar Jadhav, Arjun Barge, Nikhil Magar, " Machine Learning Based Computer Vision Application for Visually Disabled People, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 3, pp.488-494, May-June-2021. Available at doi : https://doi.org/10.32628/CSEIT2173130