An open architecture to develop a handheld device for helping visually impaired people

Battaglia, Filippo; Iannizzotto, Giancarlo

doi:10.1109/tce.2012.6311360

Cited by 9 publications

(8 citation statements)

References 21 publications

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“…According to the official documentation by Google 5 , the three major design patterns for developing software on Aerial object detection using IR sensor data by calculating distance using the triangulation method, fall detection using the six-axis gyroscope and accelerometer in smart glasses, and intelligent cane and notification system in case of fall detection Highly portable and wearable as the compute is performed by sensors on the smart glasses and intelligent cane. High reliability due to the presence of a notification mechanism in case of fall detection.…”

Section: B Proposed Application Development Methodologymentioning

confidence: 99%

“…Bradley et al [4] ex-perimented, testing whether a group of sighted individuals and visually impaired individuals experience a difference in physical and mental demands when given directions to specific landmarks. Battaglia et al [5] developed an integrated, modular, and expandable open-source package called Blind Assistant to show that it is possible to produce effective and affordable aids for the BVIP. Meza-de-Luna et al [6] designed a social-aware assistant using a pair of smart glasses and a haptic belt to enhance the face-to-face conversations of the BVIP by providing them with vibrational cues from the belt.…”

Section: Introductionmentioning

confidence: 99%

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A Google Glass Based Real-Time Scene Analysis for the Visually Impaired

et al. 2021

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Blind and Visually Impaired People (BVIP) are likely to experience difficulties with tasks that involve scene recognition. Wearable technology has played a significant role in researching and evaluating systems developed for and with the BVIP community. This paper presents a system based on Google Glass designed to assist BVIP with scene recognition tasks, thereby using it as a visual assistant. The camera embedded in the smart glasses is used to capture the image of the surroundings, which is analyzed using the Custom Vision Application Programming Interface (Vision API) from Azure Cognitive Services by Microsoft. The output of the Vision API is converted to speech, which is heard by the BVIP user wearing the Google Glass. A dataset of 5000 newly annotated images is created to improve the performance of the scene description task in Indian scenarios. The Vision API is trained and tested on this dataset, increasing the mean Average Precision (mAP) score from 63% to 84%, with an IoU > 0.5. The overall response time of the proposed application was measured to be less than 1 second, thereby providing accurate results in realtime. A Likert scale analysis was performed with the help of the BVIP teachers and students at the "Roman Catherine Lobo School for the Visually Impaired" at Mangalore, Karnataka, India. From their response, it can be concluded that the application helps the BVIP better recognize their surrounding environment in real-time, proving the device effective as a potential assistant for the BVIP.

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Section: B Proposed Application Development Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Google Glass Based Real-Time Scene Analysis for the Visually Impaired

et al. 2021

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“…A Blind Assistant, an integrated modular, expandable, open-source software package, with the goal of demonstrating that it is possible to create low-cost, highimpact assistive technology for the visually impaired by simply porting software that is currently only available for bulky personal computers [11].…”

Section: Literature Surveymentioning

confidence: 99%

Integrated Intelligent Assistant for Visually Impaired

2024

Preprint

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A person with a visual impairment finds it more difficult to recognize objects, avoid obstacles, and navigate independently. Visual impairment makes more difficult for those people to learn about their surroundings. Navigating through spaces becomes intricate, as the individual must rely on other senses and aids like canes or guide dogs to detect obstacles and safely maneuver through surroundings. Recognizing objects becomes a complex endeavor, as visual cues are limited or absent, leading to difficulties in identifying items, faces, or even familiar places. The proposed work introduces a brand-new visual assistance solution by creating a single, intelligent device that empowers visually impaired users through its multifaceted functionalities obtained by combining deep learning and machine learning algorithms. Image processing techniques such You Only Look Once (YOLO), Haar-Cascade algorithm is used for object detection and face recognition with the help of camera and other sensors. A comprehensive case study was conducted, demonstrating the real-time capabilities of YOLOv8 in detecting objects and obstacles on public roads, offering empirical evidence of its effectiveness in assisting visually impaired individuals in navigating urban environments safely and independently. The suggested prototype, in comparison to the white cane, provides the visually impaired with increased accessibility, comfort, and ease of navigation, according to the results.

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“…Çalışmaya konu olan görme engelliler için geliştirilen yardımcı cihazların yapımında kullanılan malzemeler, amacına göre farklılık göstermektedir. Buna örnek olarak, görme engelli kişilerin önündeki engelleri tespit etmesini kolaylaştırmak amacıyla kamera veya çeşitli sensörler kullanılarak yapılan yardımcı cihazlar literatürde mevcuttur [2], [3], [4], [5], [6], [7], [8], [9], [10]. Bununla beraber, gideceği güzergahı GPS ile tespit edip engelli kişiyi yönlendiren sistemler de geliştirilmiştir [11] Kişilerin sosyal hayatları düşünüldüğünde temel ihtiyaçlarını karşılamak için gerekli yetenekleri sağlayacak renk tanıma, fiyat okuma, boyutu ve uzaklığını algılama gibi özellikleri olan cihazlar da gelişen teknolojiye paralel olarak yapılmaktadır [6], [7].…”

Section: Introductionunclassified

Görme Engelliler için Vücudun Okuma Hassasiyetinin Ölçülmesi

Avşar¹,

Furat²

2020

European Journal of Science and Technology

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Öz Bilindiği gibi görme engelliler ve diğer engelli bireylerin sosyal hayata entegrasyonu yönünde birçok çalışma yapılmakta fakat yapılan çalışmaların birçoğu engelli bireylerin hareket, konfor gibi durumlarını sınırlamaktadır. Özellikle hareket kabiliyeti düşük olan görme engelli bireylerde hareket kabiliyetlerini kısıtlamayacak cihazlar geliştirilmesi ihtiyacı bulunmaktadır. Görme engelli bireylerin sosyal yaşamdaki karşılaştığı sorunları ele alındığında, birçok alanda ciddi gelişmelerin yaşandığı günümüz şartlarında, görme engelli kişilerin yeteri kadar teknolojiden faydalanmayıp, okuma yetenekleri sadece Braille alfabesi ile yazılan metinler ve sayısal ortamdaki metinleri sese çevirebilen teknolojilerden ibarettir. Her iki durumda da mobilitelerinin kısıtlı olması sebebiyle sosyal ortamdan uzak kalmaları büyük sorun teşkil etmektedir. Bunun yanı sıra, görme engelli bireylerin kullanacağı ve kültürel gelişimine katkıda bulunabilecek nitelikte materyallerin (kitap, dergi, gazete v.b) kısıtlı olması, üretilen materyallerin kullanılan alfabe tekniği nedeniyle ulaşılmasının zor olması veya maliyetinin yüksek olması sorun olmaktadır. Özellikle görme engelli bireylerin hareket kabiliyetlerini kısıtlamadan ve dış ortamdan izole olmadan dijital ortamdaki metinleri daha çok titreşim yoluyla okuma yapabilmesi için, vücutta kişinin çeşitli bölgeleri üzerinde bir çalışma yapılmış olup bu yolla yapacakları okuma hassasiyeti bu çalışmada araştırılmıştır.

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An open architecture to develop a handheld device for helping visually impaired people

Cited by 9 publications

References 21 publications

A Google Glass Based Real-Time Scene Analysis for the Visually Impaired

A Google Glass Based Real-Time Scene Analysis for the Visually Impaired

Integrated Intelligent Assistant for Visually Impaired

Görme Engelliler için Vücudun Okuma Hassasiyetinin Ölçülmesi

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