University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Blind subjects faces database

Poh, N, Blanco-Gonzalo, R, Wong, R and Sanchez-Reillo, R (2016) Blind subjects faces database IET BIOMETRICS, 5 (1). pp. 20-27.

[img] Text
BSFB--IET2015 (2).docx - Accepted version Manuscript
Available under License : See the attached licence file.

Download (1MB)
Text (licence)
Available under License : See the attached licence file.

Download (33kB) | Preview


Using your face to unlock a mobile device is not only an appealing security solution, but also a desirable or entertaining feature, such as taking selfies. It is convenient, fast, and does not require much effort, but only if you have no vision problems. For users with visual impairments, taking selfies could potentially be a challenging task. In order to study the usability and ensure the inclusion of mobile-based identity authentication technology, we have collected the Blind-Subjects Faces Data Base (BSFDB). Ensuring that technology is accessible to disabled people is important because they account for about 15% of the world population. The BSFDB database contains several individuals with visual disabilities who took selfies with a mock-up mobile device. The experimental settings vary in the image acquisition process or experimental protocol. Four experimental protocols are defined by a dichotomy of two controlled covariates, namely, whether or not a subject is guided by audio feedback and whether or not he/she has received explicit instructions to take the selfie. Our findings suggest that the importance of appropriate design of human computer interaction as well as alternative feedback design. The BSFDB database can be used to investigate topics such as usability, accessibility of the face recognition technology, or its algorithmic performance. All the gathered data is publicly available online including videos of the experiments with more than 70,000 face images of blind and partially blind subjects.

Item Type: Article
Subjects : Computer Science
Divisions : Faculty of Engineering and Physical Sciences > Computing Science
Authors :
Poh, N
Blanco-Gonzalo, R
Wong, R
Sanchez-Reillo, R
Date : 1 March 2016
DOI : 10.1049/iet-bmt.2015.0016
Copyright Disclaimer : This paper is a postprint of a paper submitted to and accepted for publication in IET BIOMETRICS and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library
Uncontrolled Keywords : Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, RECOGNITION, VOICE
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 20 Oct 2016 08:11
Last Modified : 31 Oct 2017 18:48

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800