A novel approach of assisting the visually impaired to navigate path and avoiding obstacle-collisions

Deb, Suman; Reddy, Sheetal; Baidya, Ujjwal; Sarkar, Amit; Renu, Pratik

doi:10.1109/iadcc.2013.6514385

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…vOICe system has been patented by Philips and [6] uses head mounted camera as a third eye for the blind are also available in literature. In these approaches an image is converted to sound whose loudness and frequency depends on elevation, position and brightness.…”

Section: Assistive Devices Worn On Headmentioning

confidence: 99%

Assistive aids for the disabled: Past, present and future

Chitranshi

Yadav

2014

2014 5th International Conference - Confluence the Next Generation Information Technology Summit (Confluence)

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Assistive aids have been made in the recent years to help the disabled. These include persons with visual, hearing, speech, locomotor and mental disabilities. If the technology continues to grow over the next few years the poor disabled population will have access to low cost assistive aids and may become more employable. This paper discusses the assistive aids that has been developed in the past, recent years, compares them and predicts the future assistive aids that will drive the technology for the disabled.

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Section: Assistive Devices Worn On Headmentioning

confidence: 99%

Assistive aids for the disabled: Past, present and future

Chitranshi

Yadav

2014

2014 5th International Conference - Confluence the Next Generation Information Technology Summit (Confluence)

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“…As a consequence, our solution is still able to identify objects even if they are moved from one position to another in the environment. Similarly to other approaches based on object recognition (Deb et al, 2013, Bagwan and Sankpal, 2015, Matusiak et al, 2013, our solution uses SIFT descriptors, the already existing network infrastructure of an environment, 2) Client image sent to server; 3 and 4) Check similarity of client image against images in database; 5) Fetch metadata of database image that is most similar to client image; 6) Send metadata back to mobile client, which will provide the user with an audio feedback and a smartphone to provide a low-cost contextual guidance to visually impaired users. In that light, we clearly present the processing time and limitations regarding the use of SIFT descriptors in our approach, which is not clearly discussed by previous authors.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, approaches based on object recognition try to overcome the limitations of previously mentioned works. Deb et al (2013) proposes a low-cost solution that guides VI people to detour obstacle in outdoor environments. However, any further information about the objects is not given to the user.…”

Section: Related Workmentioning

confidence: 99%

INSIDe: Image recognition tool aimed at helping visually impaired people contextualize indoor environments

Fank¹,

Bevilacqua²,

Duarte³

et al. 2019

RBCA

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Visually impaired (VI) people face a set of challenges when trying to orient and contextualize themselves. Computer vision and mobile devices can be valuable tools to help them improve their quality of life. This work presents a tool based on computer vision and image recognition to assist VI people to better contextualize themselves indoors. The tool works as follows: user takes a picture $\rho$ using a mobile application; ρ is sent to the server; ρ is compared to a database of previously taken pictures; server returns metadata of the database image that is most similar to ρ; finally the mobile application gives an audio feedback based on the received metadata. Similarity test among database images and $\rho$ is based on the search of nearest neighbors in key points extracted from the images by SIFT descriptors. Three experiments are presented to support the feasibility of the tool. We believe our solution is a low cost, convenient approach that can leverage existing IT infrastructure, e.g. wireless networks, and does not require any physical adaptation in the environment where it will be used.

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“…The idea proposed by Deb et al (2013) aims predominantly at the safe navigation of the VIP by estimating the safe direction in which they can walk. In the project, authors use a simple camera for image acquisition and apply techniques such as edge detection and pyramidal segmentation to then define a safe zone using Template Matching and transmit via musical tones whether the safe path is to the right or left.…”

Section: Related Workmentioning

confidence: 99%

Embedded Navigation and Classification System for Assisting Visually Impaired People

Dourado

Pedrino

2018

Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application

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Loss of vision has a large detrimental impact on a person's mobility. Every day, visually impaired people (VIPs) face various challenges just to get around in the most diverse environments. Technological solutions, called Electronic Travel Aids, help a VIP with these challenges, giving greater confidence in the task of getting around in unfamiliar surroundings. Thus, this article presents an embedded navigation and classification system for helping VIPs indoors. Using stereo vision, the system is able to detect obstacles and choose safe ways for the VIP to walk around without colliding. A convolutional neural network using a graphics processing unit (GPU) classifies the obstacles. Acoustic feedback is transmitted to the VIP. The article also features a wearable prototype, to which the system hardware is docked for use. Using the system, the prototype could detect and classify obstacles in real time defining free paths, all with battery autonomy of about 6 hours.

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A novel approach of assisting the visually impaired to navigate path and avoiding obstacle-collisions

Cited by 5 publications

References 9 publications

Assistive aids for the disabled: Past, present and future

Assistive aids for the disabled: Past, present and future

INSIDe: Image recognition tool aimed at helping visually impaired people contextualize indoor environments

Embedded Navigation and Classification System for Assisting Visually Impaired People

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