A Wearable Vision-To-Audio Sensory Substitution System Based on Deep Learning for the Visually Impaired

Author(s):  
Zifeng Wang ◽  
Heng Li ◽  
Jianpin Chen ◽  
Xinyu Chai ◽  
Zhenzhen Zhai
Author(s):  
Mariacarla Memeo ◽  
Marco Jacono ◽  
Giulio Sandini ◽  
Luca Brayda

Abstract Background In this work, we present a novel sensory substitution system that enables to learn three dimensional digital information via touch when vision is unavailable. The system is based on a mouse-shaped device, designed to jointly perceive, with one finger only, local tactile height and inclination cues of arbitrary scalar fields. The device hosts a tactile actuator with three degrees of freedom: elevation, roll and pitch. The actuator approximates the tactile interaction with a plane tangential to the contact point between the finger and the field. Spatial information can therefore be mentally constructed by integrating local and global tactile cues: the actuator provides local cues, whereas proprioception associated with the mouse motion provides the global cues. Methods The efficacy of the system is measured by a virtual/real object-matching task. Twenty-four gender and age-matched participants (one blind and one blindfolded sighted group) matched a tactile dictionary of virtual objects with their 3D-printed solid version. The exploration of the virtual objects happened in three conditions, i.e., with isolated or combined height and inclination cues. We investigated the performance and the mental cost of approximating virtual objects in these tactile conditions. Results In both groups, elevation and inclination cues were sufficient to recognize the tactile dictionary, but their combination worked at best. The presence of elevation decreased a subjective estimate of mental effort. Interestingly, only visually impaired participants were aware of their performance and were able to predict it. Conclusions The proposed technology could facilitate the learning of science, engineering and mathematics in absence of vision, being also an industrial low-cost solution to make graphical user interfaces accessible for people with vision loss.


2020 ◽  
Vol 9 (3) ◽  
pp. 1208-1219
Author(s):  
Hendra Kusuma ◽  
Muhammad Attamimi ◽  
Hasby Fahrudin

In general, a good interaction including communication can be achieved when verbal and non-verbal information such as body movements, gestures, facial expressions, can be processed in two directions between the speaker and listener. Especially the facial expression is one of the indicators of the inner state of the speaker and/or the listener during the communication. Therefore, recognizing the facial expressions is necessary and becomes the important ability in communication. Such ability will be a challenge for the visually impaired persons. This fact motivated us to develop a facial recognition system. Our system is based on deep learning algorithm. We implemented the proposed system on a wearable device which enables the visually impaired persons to recognize facial expressions during the communication. We have conducted several experiments involving the visually impaired persons to validate our proposed system and the promising results were achieved.


Author(s):  
G. Touya ◽  
F. Brisebard ◽  
F. Quinton ◽  
A. Courtial

Abstract. Visually impaired people cannot use classical maps but can learn to use tactile relief maps. These tactile maps are crucial at school to learn geography and history as well as the other students. They are produced manually by professional transcriptors in a very long and costly process. A platform able to generate tactile maps from maps scanned from geography textbooks could be extremely useful to these transcriptors, to fasten their production. As a first step towards such a platform, this paper proposes a method to infer the scale and the content of the map from its image. We used convolutional neural networks trained with a few hundred maps from French geography textbooks, and the results show promising results to infer labels about the content of the map (e.g. ”there are roads, cities and administrative boundaries”), and to infer the extent of the map (e.g. a map of France or of Europe).


2019 ◽  
Author(s):  
Jamie E. Poole ◽  
Jhon P. C. Casas ◽  
Roberto A. Bolli ◽  
Hermano I. Krebs

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