Do-It-Yourself Object Identification Using Augmented Reality for Visually Impaired People

2012 ◽  
pp. 560-565 ◽  
Author(s):  
Atheer S. Al-Khalifa ◽  
Hend S. Al-Khalifa
Keyword(s):  
Augmented Reality ◽  
Visually Impaired ◽  
Object Identification ◽  
Visually Impaired People ◽  
Impaired People ◽  
Do It Yourself

scholarly journals A Navigation and Augmented Reality System for Visually Impaired People

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3061
Author(s):  
Alice Lo Valvo ◽  
Daniele Croce ◽  
Domenico Garlisi ◽  
Fabrizio Giuliano ◽  
Laura Giarré ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Visually Impaired ◽  
Virtual Path ◽  
Physical Support ◽  
Augmented Reality System ◽  
Virtual Paths ◽  
Visually Impaired People ◽  
Impaired People ◽  
Autonomous Mobility ◽  
Indoor And Outdoor

In recent years, we have assisted with an impressive advance in augmented reality systems and computer vision algorithms, based on image processing and artificial intelligence. Thanks to these technologies, mainstream smartphones are able to estimate their own motion in 3D space with high accuracy. In this paper, we exploit such technologies to support the autonomous mobility of people with visual disabilities, identifying pre-defined virtual paths and providing context information, reducing the distance between the digital and real worlds. In particular, we present ARIANNA+, an extension of ARIANNA, a system explicitly designed for visually impaired people for indoor and outdoor localization and navigation. While ARIANNA is based on the assumption that landmarks, such as QR codes, and physical paths (composed of colored tapes, painted lines, or tactile pavings) are deployed in the environment and recognized by the camera of a common smartphone, ARIANNA+ eliminates the need for any physical support thanks to the ARKit library, which we exploit to build a completely virtual path. Moreover, ARIANNA+ adds the possibility for the users to have enhanced interactions with the surrounding environment, through convolutional neural networks (CNNs) trained to recognize objects or buildings and enabling the possibility of accessing contents associated with them. By using a common smartphone as a mediation instrument with the environment, ARIANNA+ leverages augmented reality and machine learning for enhancing physical accessibility. The proposed system allows visually impaired people to easily navigate in indoor and outdoor scenarios simply by loading a previously recorded virtual path and providing automatic guidance along the route, through haptic, speech, and sound feedback.

scholarly journals Object Identification and Safe Route Recommendation Based on Human Flow for the Visually Impaired

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5343 ◽  
Author(s):  
Yusuke Kajiwara ◽  
Haruhiko Kimura
Keyword(s):  
Visually Impaired ◽  
Object Identification ◽  
Obstacle Detection ◽  
World Health ◽  
Detection Methods ◽  
Monocular Camera ◽  
Visually Impaired People ◽  
Average Accuracy ◽  
Impaired People ◽  
Health Organization

It is difficult for visually impaired people to move indoors and outdoors. In 2018, world health organization (WHO) reported that there were about 253 million people around the world who were moderately visually impaired in distance vision. A navigation system that combines positioning and obstacle detection has been actively researched and developed. However, when these obstacle detection methods are used in high-traffic passages, since many pedestrians cause an occlusion problem that obstructs the shape and color of obstacles, these obstacle detection methods significantly decrease in accuracy. To solve this problem, we developed an application “Follow me!”. The application recommends a safe route by machine learning the gait and walking route of many pedestrians obtained from the monocular camera images of a smartphone. As a result of the experiment, pedestrians walking in the same direction as visually impaired people, oncoming pedestrians, and steps were identified with an average accuracy of 0.92 based on the gait and walking route of pedestrians acquired from monocular camera images. Furthermore, the results of the recommended safe route based on the identification results showed that the visually impaired people were guided to a safe route with 100% accuracy. In addition, visually impaired people avoided obstacles that had to be detoured during construction and signage by walking along the recommended route.

scholarly journals Eye(I) Still Know! – An App for the Blind Built using Web and AI

2021 ◽  
Vol 11 (2) ◽  
pp. 218-224
Author(s):  
Akshata Sangwai ◽  
Shriya Deshmukh ◽  
Vardaan Sathe ◽  
Rishika Agarwal ◽  
Rakhi Kalantri
Keyword(s):  
Visually Impaired ◽  
Voice Recognition ◽  
Object Identification ◽  
Control Solution ◽  
Image Scanning ◽  
Visually Impaired People ◽  
Voice Control ◽  
The World ◽  
Impaired People ◽  
Audio Output

This paper proposes eye(I) still know!, a voice control solution for the visually impaired people. The main purpose is even though the blind cannot see they can still know where to go and what to do! Nearby 60% of total blind population across the world is present in India. In a time where no one likes to rely on anyone, this is a small effort to make the blind independent individuals. This can be achieved using wireless communication, voice recognition and image scanning. The application with the use of object identification will priorly inform about the barriers in the path. The software will use the camera of the device and scan all the obstacles with their corresponding distances from the user. This will be followed by audio instructions through audio output of the device. This will efficiently direct the user through his/her way.

scholarly journals It is Indeed Time to Focus on Ai Based Image Recognizing App to Boost the Self-Confidence of the Visually Challenged in the Indian Context

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1267-1274
Keyword(s):  
Visually Impaired ◽  
Object Identification ◽  
The Self ◽  
Self Confidence ◽  
Indian Context ◽  
Visually Impaired People ◽  
Impaired People ◽  
Before And After ◽  
Marginal Improvement ◽  
Visually Impaired Persons

Purpose: Artificial intelligence (AI) will be at the forefront of any modern communication in the future, so this research is carried out to find out the strengths and limitations of the AI based image recognizing app (AI poly) for the visually impaired people and also to assess the self-confidence of such people before and after using the app Methodology: 40 visually impaired people from the Atmadeepam Society (Nagpur, India) who are computer - educated and smartphone users considered for the study using mixed research methods. For measuring the app usability, InApp survey is undertaken and for finding the self-confidence; ASCI inventory is done Findings: More than 80% of the respondents are satisfied with the app however; this does not hold true for the Indian food items recognizing feature of the app as the satisfaction is as low as 63%. There is a marginal improvement seen in their self-confidence post regularly using this app for three months Practical Implications: It is evident from the findings that these visually impaired people are extremely happy in using this AI poly app to overcome their navigation challenges and get confidence in doing their own things independently On the other hand, research finding also shows a set of people who are not convinced fully with the AI based apps functioning. These were typically based on incorrect object identification, difficulty in understanding the accent of the voice assistants Social Implications: The visually impaired will be better equipped to function due to increased confidence, positive attitude and thus gaining a place in society as an active contributor to the economy, which will contribute to the Disabilities integration Originality / Value: The paper attempts to study modern AI accessibility applications for visually impaired persons, in particular related to object recovery in the Indian context. And to assess their self-confidence post using the app.

Application of IoT Based Stick for Visually Impaired People in CVIS System

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Ammar Muhammad ◽  
Qizhou Hu ◽  
Muhammad Tayyab ◽  
Yikai Wu ◽  
Muhammad Ahtsham
Keyword(s):  
Visually Impaired ◽  
Visually Impaired People ◽  
Impaired People
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