Development of a wearable guide device based on convolutional neural network for blind or visually impaired persons

Hsieh, Yi-Zeng; Lin, Shih-Syun; Xu, Fu-Xiong

doi:10.1007/s11042-020-09464-7

Cited by 27 publications

(15 citation statements)

References 40 publications

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“…Various kinds of NNs(Neural Networks), like CNNs [32] and RNNs [33], have been implemented showing the effectiveness of monocular depth estimation. In [34], a CNN network is used for calculating the distance of the obstacles. Their method works more accurate than some devices like Kinect, according to their comparisons.…”

Section: Obstacle Detectionmentioning

confidence: 99%

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

Valipoor

Jiménez

2022

Univ Access Inf Soc

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During the past years, the development of assistive technologies for visually impaired (VI)/blind people has helped address various challenges in their lives by providing services such as obstacle detection, indoor/outdoor navigation, scene description, text reading, facial recognition and so on. This systematic mapping review is mainly focused on the scene understanding aspect (e.g., object recognition and obstacle detection) of assistive solutions. It provides guidance for researchers in this field to understand the advances during the last four and a half years. This is because deep learning techniques together with computer vision have become more powerful and accurate than ever in tasks like object detection. These advancements can bring a radical change in the development of high-quality assistive technologies for VI/blind users. Additionally, an overview of the current challenges and a comparison between different solutions is provided to indicate the pros and cons of existing approaches.

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Section: Obstacle Detectionmentioning

confidence: 99%

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

Valipoor

Jiménez

2022

Univ Access Inf Soc

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“…In terms of technology, 'assistive technology' can be regarded as a general term, so the keyword appeared more frequently and stands as a root of the map in Figure 7. Subsequently, specific technologies emerged for services with explicit demands, such as ultrasonic sensors [32], infrared sensors [33], computer vision [34], ultrawideband (UWB) [35], and GPS [36] to collect environmental information; image processing [37], convolutional neural network (CNN) [38], and deep learning [14] to achieve advanced intelligence; stereo audio [39], audio-tactile maps [40], and haptic feedbacks [41] to bridge humans and machines. From the perspective of requirement, 'accessibility', 'mobility', and 'wearable' are among the most popular keywords.…”

Section: Primary Topics and Research Hotspots By Keyword Co-occurrencementioning

confidence: 99%

A Bibliometric Narrative Review on Modern Navigation Aids for People with Visual Impairment

et al. 2021

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The innovations in the field of specialized navigation systems have become prominent research topics. As an applied science for people with special needs, navigation aids for the visually impaired are a key sociotechnique that helps users to independently navigate and access needed resources indoors and outdoors. This paper adopts the informetric analysis method to assess the current research and explore trends in navigation systems for the visually impaired based on bibliographic records retrieved from the Web of Science Core Collection (WoSCC). A total of 528 relevant publications from 2010 to 2020 were analyzed. This work answers the following questions: What are the publication characteristics and most influential publication sources? Who are the most active and influential authors? What are their research interests and primary contributions to society? What are the featured key studies in the field? What are the most popular topics and research trends, described by keywords? Additionally, we closely investigate renowned works that use different multisensor fusion methods, which are believed to be the bases of upcoming research. The key findings of this work aim to help upcoming researchers quickly move into the field, as they can easily grasp the frontiers and the trend of R&D in the research area. Moreover, we suggest the researchers embrace smartphone-based agile development, as well as pay more attention to phone-based prominent frameworks such as ARCore or ARKit, to achieve a fast prototyping for their proposed systems. This study also provides references for the associated fellows by highlighting the critical junctures of the modern assistive travel aids for people with visual impairments.

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“…Object detection has been a popular area of research over the past few decades, as indicated by the large number of new applications related to identifying objects based on visual detection, such as facial expression recognition, (2) navigation assistants, (3) autonomous robot navigation, (4) self-driving systems, (5) image recognition, (6) and pedestrian detection. (7) Many approaches have been used to assist visually impaired people in obtaining information on a digital platform.…”

Section: Related Workmentioning

confidence: 99%

Interactive Sound Generation to Aid Visually Impaired People via Object Detection Using Touch Screen Sensor

Kurniati¹,

Yang²,

Chen³

et al. 2021

Sensors and Materials

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Along with the invention of portable devices, such as smartphones and tablets, computerbased touch screen sensor-assistive technologies have become significantly more affordable than traditional tactile graphics. The sensor panel in these technologies allows users to receive visual and auditorial responses via interaction with the device. However, visually impaired individuals (with a lack or loss of ability to see) will not find visual responses useful when using tablets or smartphones. Therefore, in this paper we propose a system that helps visually impaired people comprehend information on electronic devices with the help of auditory action feedback. We develop a multimedia system for sound production from a given image via object detection. In this study, YOLO (You Only Look Once) is used in object detection for sonification. A pretrained model is used; thus, a wider range of object classification can be identified. The system generates the corresponding sound when an object on the sensor screen is touched. The purpose of our research is to aid visually impaired people to perceive information of a picture shown on the device by touching the detected object. The device was tested by simulating visually impaired people by blindfolding people with normal vision, who filled out questionnaires on its performance. The results indicate that most of the users found that the sound presented by the device was helpful for telling them what the shown image was.

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Development of a wearable guide device based on convolutional neural network for blind or visually impaired persons

Cited by 27 publications

References 40 publications

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

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

A Bibliometric Narrative Review on Modern Navigation Aids for People with Visual Impairment

Interactive Sound Generation to Aid Visually Impaired People via Object Detection Using Touch Screen Sensor

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