scholarly journals Blindfold: A Smartphone based Object Detection Application

2021 ◽  
Vol 9 (VI) ◽  
pp. 1268-1273
Author(s):  
Rishabh Sharma
Keyword(s):  
Assistive Technology ◽  
Object Detection ◽  
Visually Impaired ◽  
Computing Power ◽  
Size Accuracy

With the advancement of computing power of Smartphones, they seem to be a better option to be used as an Assistive Technology for the visually impaired. In this paper we have discussed an application which allows visually impaired users to detect objects of their choice in their environment. We have made use of the Tensorflow Lite Application Programmable Interface (API), an API by Tensorflow which specifically runs models on an Android Smartphone. We have discussed the architecture of the API and the application itself. We have discussed the performance of various types of models such as MobileNet, ResNet & Inception. We have compared the results of the various Models on their size, accuracy & inference time(ms) and found that the MobileNet has the best performance. We have also explained the working of our application in detail.

scholarly journals High-Tech Eyes

2017 ◽  
Vol 139 (03) ◽  
pp. 36-41
Author(s):  
John Kosowatz
Keyword(s):  
Visually Impaired ◽  
High Tech ◽  
Visuomotor Integration ◽  
Computing Power ◽  
Daily Routines ◽  
Visually Impaired People ◽  
Detection Software ◽  
Tactile Navigation ◽  
The Temple ◽  
Outer Garment

This article provides an overview of high-tech sensors, visual detection software, and mobile computing power applications, which are being developed to enable visually impaired people to navigate. By adapting technology developed for robots, automobiles, and other products, researchers and developers are creating wearable devices that can aid the visually impaired as they navigate through their daily routines—even identifying people and places. The Eyeronman system, developed by NYU’s Visuomotor Integration Laboratory and Tactile Navigation Tools, combines a sensor-laden outer garment or belt with a vest studded with vibrating actuators. The sensors detect objects in the immediate environment and relay their locations via buzzes on the wearer's torso. OrCam’s, a computer vision company in Jerusalem, team of programmers, computer engineers, and hardware designers have developed MyEye device, which attaches to the temple of a pair of eyeglasses. The device instructs the user on how to store items in memory, including things such as credit cards and faces of friends and family.

Object Detection to Assist Visually Impaired People: A Deep Neural Network Adventure

2018 ◽  
pp. 500-510 ◽  
Author(s):  
Fereshteh S. Bashiri ◽  
Eric LaRose ◽  
Jonathan C. Badger ◽  
Roshan M. D’Souza ◽  
Zeyun Yu ◽  
...  
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Visually Impaired ◽  
Deep Neural Network ◽  
Visually Impaired People ◽  
Impaired People

scholarly journals Real Time Object Detection Canbe Embedded on Low Powered Devices

2019 ◽  
Author(s):  
Jimut Bahan Pal
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Open Source ◽  
Real Time ◽  
Detection System ◽  
Computing Power ◽  
Convolution Neural Networks ◽  
Real Challenge ◽  
New Algorithms

It has been a real challenge for computers with low computing power and memory to detect objects in real time. After the invention of Convolution Neural Networks (CNN) it is easy for computers to detect images and recognize them. There are several technologies and models which can detect objects in real time, but most of them require high end technologies in terms of GPUs and TPUs. Though, recently many new algorithms and models have been proposed, which runs on low resources. In this paper we studied MobileNets to detect objects using webcam to successfully build a real time objectdetection system. We observed the pre trained model of the famous MS COCO dataset to achieve our purpose. Moreover, we applied Google’s open source TensorFlow as our back end. This real time object detection system may help in future to solve various complex vision problems.

A Guide to Assistive Technology for Teachers in Special Education

2012 ◽  
pp. 105-118 ◽  
Author(s):  
Harris Wang
Keyword(s):  
Special Education ◽  
Distance Learning ◽  
Assistive Technology ◽  
Learning Disability ◽  
Visually Impaired ◽  
Assistive Technologies ◽  
The Internet ◽  
Web Based ◽  
The Right ◽  
Hearing Difficulties

Everyone has the right to learn and to succeed in education. For people with certain disabilities, learning can be a challenging task, and proper use of certain assistive technologies can significantly ease the challenge, and help the learners to succeed. For teachers in special education, knowing existing assistive technology is an important step towards the proper use of those technologies and success in special education. This chapter provides a guide for teachers about assistive technology and its uses in special education. Assistive technology for people with learning difficulties, assistive technology for the visually impaired, and assistive technology for people with hearing difficulties will be discussed. Since online learning and the Internet are becoming trends in distance education, this chapter will focus on assistive technologies for Web-based distance learning, including assistive technologies for better human-computer interaction. Selecting more appropriate assistive technology for a given learner with a certain learning disability, among many choices, will be discussed.

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