Wearable Obstacle Avoidance Electronic Travel Aids for Blind: A Survey

Dakopoulos, D.; Bourbakis, Nikolaos G.

doi:10.1109/tsmcc.2009.2021255

Cited by 524 publications

(247 citation statements)

References 22 publications

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“…In the last 50 years there have been many efforts to develop electronic aids to improve quality of life and the safety of individuals with special needs [4, 6, 21, 22, 29, 30, 34-36, 38, 39, 45-47]. Several techniques have been developed to identify banknotes from camera captured images for helping blind or visually impaired people.…”

Section: Related Workmentioning

confidence: 99%

Robust and Effective Component-Based Banknote Recognition for the Blind

Hasanuzzaman

Yang

Tian

2012

IEEE Trans. Syst., Man, Cybern. C

106

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We develop a novel camera-based computer vision technology to automatically recognize banknotes for assisting visually impaired people. Our banknote recognition system is robust and effective with the following features: 1) high accuracy: high true recognition rate and low false recognition rate, 2) robustness: handles a variety of currency designs and bills in various conditions, 3) high efficiency: recognizes banknotes quickly, and 4) ease of use: helps blind users to aim the target for image capture. To make the system robust to a variety of conditions including occlusion, rotation, scaling, cluttered background, illumination change, viewpoint variation, and worn or wrinkled bills, we propose a component-based framework by using Speeded Up Robust Features (SURF). Furthermore, we employ the spatial relationship of matched SURF features to detect if there is a bill in the camera view. This process largely alleviates false recognition and can guide the user to correctly aim at the bill to be recognized. The robustness and generalizability of the proposed system is evaluated on a dataset including both positive images (with U.S. banknotes) and negative images (no U.S. banknotes) collected under a variety of conditions. The proposed algorithm, achieves 100% true recognition rate and 0% false recognition rate. Our banknote recognition system is also tested by blind users.

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Section: Related Workmentioning

confidence: 99%

Robust and Effective Component-Based Banknote Recognition for the Blind

Hasanuzzaman

Yang

Tian

2012

IEEE Trans. Syst., Man, Cybern. C

106

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“…In recent years, many electronic travel aids (ETA), especially vision-based obstacle avoidance systems, have been developed to help the visually impaired people to walk safely [1,2]. Vision-based obstacle detection is one of the major issues that need to be considered to ensure safe navigation of visually impaired people.…”

Section: Introductionmentioning

confidence: 99%

Indoor/outdoor navigation system based on possibilistic traversable area segmentation for visually impaired people

Elleuch¹,

Sellami²,

Kallel³

2016

ELCVIA

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Autonomous collision avoidance for visually impaired people requires a specific processing for an accurate definition of traversable area. Processing of a real time image sequence for traversable area segmentation is mandatory. Low cost systems suggest use of poor quality cameras. However, low cost camera suffers from great variability of traversable area appearance at indoor as well as outdoor environments. Taking into account ambiguity affecting object and traversable area appearance induced by reflections, illumination variations, occlusions (, etc...), an accurate segmentation of traversable area in such conditions remains a challenge. Moreover, at indoor and outdoor environments, more added variability is induced. In this paper, we present a fast traversable area segmentation approach from image sequence recorded by a low-cost monocular camera for navigation system. Taking into account all kinds of variability in the image, we apply possibility theory for modeling information ambiguity. An efficient way of updating the traversable area model in each environment condition is to consider traversable area samples from the same processed image for building its possibility maps. Then fusing these maps allows making a fair model definition of the traversable area. Performance of the proposed system was evaluated on public databases, at indoor and outdoor environments. Experimental results show that this method is challenging leading to higher segmentation rates.

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“…Recently, more technological solutions have been developed to support the autonomous mobility of visually impaired people [2]. Yet currently, proposed methods tend to not completely fulfill all the user requirements, so that visually impaired people are usually skeptical about them, and not keen to replace traditional solutions.…”

Section: Introductionmentioning

confidence: 99%

Smartphone-Based Obstacle Detection for the Visually Impaired

Caldini

Fanfani

Colombo

2015

Lecture Notes in Computer Science

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Abstract.One of the main problems that visually impaired people have to deal with is moving autonomously in an unknown environment. Currently, the most used autonomous walking aid is still the white can. Though in the last few years more technological devices have been introduced, referred to as electronic travel aids (ETAs). In this paper, we present a novel ETA based on computer vision. Exploiting the hardware and software facilities of a standard smartphone, our system is able to extract a 3D representation of the scene and detect possible obstacles. To achieve such a result, images are captured by the smartphone camera and processed with a modified Structure from Motion algorithm that takes as input also information from the built-in gyroscope. Then the system estimates the ground-plane and labels as obstacles all the structures above it. Results on indoor and outdoor test sequences show the effectiveness of the proposed method.

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Wearable Obstacle Avoidance Electronic Travel Aids for Blind: A Survey

Cited by 524 publications

References 22 publications

Robust and Effective Component-Based Banknote Recognition for the Blind

Robust and Effective Component-Based Banknote Recognition for the Blind

Indoor/outdoor navigation system based on possibilistic traversable area segmentation for visually impaired people

Smartphone-Based Obstacle Detection for the Visually Impaired

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