Independent mobility is one of the main challenges for blind or visually impaired (BVI) people. In particular, BVI people often need to identify and avoid nearby obstacles, for example a bicycle parked on the sidewalk. This is generally achieved with a combination of residual vision, hearing and haptic sensing using the white cane. However, in many cases, BVI people can only perceive obstacles at short distance (typically about 1m, i.e., the white cane detection range), in other situations obstacles are hard to detect(e.g., those elevated from the ground), while others should not be hit by the white cane(e.g., a standing person). Thus, sometime and effort are required to identify the object in order to understand how to avoid it. A solution to these problems can be found in recent computer vision techniques that can run on mobile and wearable devices to detect obstacles at a distance. However, in addition to detecting obstacles, it is also necessary to convey information about them to a BVI user. This contribution presents WatchOut, a sonifcation technique for conveying real-time information about the main characteristics of an obstacle to a BVI person, who can then use this additional feedback to safely navigate in the environment. WatchOut was designed with a user-centric approach, involving two iterations of online questionnaires with BVI participants in order to define, improve and evaluate the sonifcation technique. WatchOut was implemented and tested as a module of a mobile app that detects obstacles using state-of-the-art computer vision technology. Results show that the system is considered usable, and can guide the users to avoid more than 85% of the obstacles.

WatchOut: Obstacle Sonification for People with Visual Impairment or Blindness / D. Ahmetovic, F. Avanzini, A. Baratè, C. Bernareggi, M. Ducci, L.A. Ludovico, S. Mascetti, G. Presti - In: ASSETS '19[s.l] : ACM, 2019. - ISBN 9781450366762. - pp. 402-413 (( Intervento presentato al 21. convegno International ACM SIGACCESS Conference on Computers and Accessibility tenutosi a Pittsburgh nel 2019 [10.1145/3308561.3353779].

WatchOut: Obstacle Sonification for People with Visual Impairment or Blindness

D. Ahmetovic;F. Avanzini;A. Baratè;C. Bernareggi;L.A. Ludovico;S. Mascetti;G. Presti
2019

Abstract

Independent mobility is one of the main challenges for blind or visually impaired (BVI) people. In particular, BVI people often need to identify and avoid nearby obstacles, for example a bicycle parked on the sidewalk. This is generally achieved with a combination of residual vision, hearing and haptic sensing using the white cane. However, in many cases, BVI people can only perceive obstacles at short distance (typically about 1m, i.e., the white cane detection range), in other situations obstacles are hard to detect(e.g., those elevated from the ground), while others should not be hit by the white cane(e.g., a standing person). Thus, sometime and effort are required to identify the object in order to understand how to avoid it. A solution to these problems can be found in recent computer vision techniques that can run on mobile and wearable devices to detect obstacles at a distance. However, in addition to detecting obstacles, it is also necessary to convey information about them to a BVI user. This contribution presents WatchOut, a sonifcation technique for conveying real-time information about the main characteristics of an obstacle to a BVI person, who can then use this additional feedback to safely navigate in the environment. WatchOut was designed with a user-centric approach, involving two iterations of online questionnaires with BVI participants in order to define, improve and evaluate the sonifcation technique. WatchOut was implemented and tested as a module of a mobile app that detects obstacles using state-of-the-art computer vision technology. Results show that the system is considered usable, and can guide the users to avoid more than 85% of the obstacles.
Sonifcation; visual impairment; obstacle avoidance; navigation assistive technologies
Settore INF/01 - Informatica
2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/687254
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