Recent trends in computer vision-driven scene understanding for VI/blind users: a systematic mapping

Valipoor, Mohammad Moeen; Jiménez, Antonio

doi:10.1007/s10209-022-00868-w

Cited by 19 publications

(8 citation statements)

References 139 publications

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“…This allows visually impaired individuals to engage with and navigate their surroundings. By combining image recognition, object detection, and scene analysis, AI-enabled applications deliver real-time environmental descriptions, identify obstacles, and support autonomous navigation (Bharath, 2022;Patthanajitsilp and Chongstitvatana, 2022;Yang et al, 2022;Valipoor and de Antonio, 2023). This recent visual understanding empowers individuals to independently move through spaces, identify objects, and engage with their surroundings in ways that were previously inaccessible.…”

Section: Computer Vision For Illuminating the Visual Realmmentioning

confidence: 99%

A Conceptual Model for Inclusive Technology: Advancing Disability Inclusion through Artificial Intelligence

Almufareh,

Kausar,

Humayun

et al. 2024

Journal of Disability Research

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Artificial intelligence (AI) has ushered in transformative changes, championing inclusion and accessibility for individuals with disabilities. This article delves into the remarkable AI-driven solutions that have revolutionized their lives across various domains. From assistive technologies such as voice recognition and AI-powered smart glasses catering to diverse needs, to healthcare benefiting from early disease detection algorithms and wearable devices that monitor vital signs and alert caregivers in emergencies, AI has steered in significant enhancements. Moreover, AI-driven prosthetics and exoskeletons have substantially improved mobility for those with limb impairments. The realm of education has not been left untouched, with AI tools creating inclusive learning environments that adapt to individual learning styles, paving the way for academic success among students with disabilities. However, the boundless potential of AI also presents ethical concerns and challenges. Issues like safeguarding data privacy, mitigating algorithmic bias, and bridging the digital divide must be thoughtfully addressed to fully harness AI’s potential in empowering individuals with disabilities. To complement these achievements, a robust conceptual model for AI disability inclusion serves as the theoretical framework, guiding the development of tailored AI solutions. By striking a harmonious balance between innovation and ethics, AI has the power to significantly enhance the overall quality of life for individuals with disabilities across a spectrum of vital areas.

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Section: Computer Vision For Illuminating the Visual Realmmentioning

confidence: 99%

A Conceptual Model for Inclusive Technology: Advancing Disability Inclusion through Artificial Intelligence

Almufareh,

Kausar,

Humayun

et al. 2024

Journal of Disability Research

View full text Add to dashboard Cite

show abstract

“…Clinical specialists can train and guide visually impaired patients on how to use the device effectively. Smart glasses such as eSight can be an alternative to costly and complicated eye procedures and treatments for visually impaired individuals, supporting them at work, in study, and day-to-day life [6] [7].…”

Section: How Can Smart Glasses Assist Visually Impaired Individuals I...mentioning

confidence: 99%

Functional Analysis and statistical Mechanics for exploring the Potential of Smart Glasses: An Assessment of Visually Impaired Individuals

Shraddha Gugulothu

2024

cana

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Using functional analysis, statistical mechanics, and deep learning (DL) methods, this study looks at how smart glasses might help people who are blind or have low vision. Smart glasses, which have advanced sensors, adaptable algorithms, and deep learning capabilities, can greatly improve the movement and independence of people who are blind or have low vision. For the most part, the study is looking at how these gadgets work, how they affect daily life, and how people interact with them by using a complex statistics approach. Using functional analysis, we break down how smart glasses work and how they're designed to be comfortable to wear, showing how flexible and easy to use they are. Statistical mechanics is a solid way to model how these gadgets will likely behave and how well they will work in different situations. Deep learning techniques are also used to improve the smart glasses' ability to recognize objects and understand their surroundings. This makes them much more accurate and quick in real time. A wide range of visually impaired people are taking part in the study, which gives a full picture of how well and how easily smart glasses work for all age groups. Real-life usage cases, feedback polls, and performance tracking are all used to collect data that lets us look at the technology's pros and cons as a whole. Preliminary results show big gains in spatial awareness, avoiding obstacles, and recognizing objects. This suggests that smart glasses with built-in DL methods can make the lives of visually blind people a lot better. Combining functional analysis, statistical mechanics, and deep learning gives us a more complete picture of the pros and cons of smart glasses, which opens the door for new developments in helpful technology in the future. This study shows how important user-centered design, advanced analysis methods, and cutting-edge DL techniques are for making solutions that help people who are blind or have low vision.

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“…A mental model refers to the outcome of the cognitive process of constructing visual impressions based on sensory input from the surroundings (Masal et al, 2023). The act of creating a mental representation is often known as "visualizing", "mentally perceiving", "auditory imagination", "imagining tactile sensations", and so on (Valipoor and De Antonio, 2023). In order to form a mental model, a person engages in cognitive processes such as simulations, reproductions, or reconstructions of previous perceptual encounters or the anticipation of future ones.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Review on Developing Computer Programming Skills for Visually Impaired Students

Aljarallah,

Dutta

2024

Journal of Disability Research

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Technology and digital-based learning drive contemporary computer skill (CS) education advances. The absence of resources that are easily accessible and tailored to help the development of conceptual understanding in computers may present a number of issues for students who have visual impairments (VI) in the context of CS education. The objective of the research was to provide a concise overview of the existing evidence-based information about CS instruction for students with severe VI. A systematic review was performed to analyze the research papers published between January 2000 and September 2023. A total of 21 articles were extracted and classified into assistive technologies (ATs) and CSs. The study findings highlight the significance of the development of ATs and effective course design for supporting individuals with VI. It can be used by policy makers and educational institutions to present a useful environment for individuals with VI to improve their CSs. In future, the authors need to focus on ATs to enhance the computer programming abilities of students with VI. In addition, they will develop programming platforms and integrated development environments that are easily accessible and can be customized to meet a wide range of learning requirements.

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Recent trends in computer vision-driven scene understanding for VI/blind users: a systematic mapping

Cited by 19 publications

References 139 publications

A Conceptual Model for Inclusive Technology: Advancing Disability Inclusion through Artificial Intelligence

A Conceptual Model for Inclusive Technology: Advancing Disability Inclusion through Artificial Intelligence

Functional Analysis and statistical Mechanics for exploring the Potential of Smart Glasses: An Assessment of Visually Impaired Individuals

A Systematic Review on Developing Computer Programming Skills for Visually Impaired Students

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