Authors:
Laurindo de Sousa Britto Neto
1
;
Vanessa Regina Margareth Lima Maike
2
;
Fernando Luiz Koch
3
;
Maria Cecília Calani Baranauskas
2
;
Anderson de Rezende Rocha
2
and
Siome Klein Goldenstein
2
Affiliations:
1
Federal University of Piauí (UFPI) and University of Campinas (UNICAMP), Brazil
;
2
University of Campinas (UNICAMP), Brazil
;
3
Samsung Research Institute, Brazil
Keyword(s):
Human-Computer Interaction, Assistive Technology, Computer Vision, Accessibility, Wearable Device.
Related
Ontology
Subjects/Areas/Topics:
Accessibility and Usability
;
Enterprise Information Systems
;
Human-Computer Interaction
;
Interaction Techniques and Devices
Abstract:
Practitioners usually expect that real-time computer vision systems such as face recognition systems will
require hardware components with high processing power. In this paper, we present a concept to show that
it is technically possible to develop a simple real-time face recognition system in a wearable device with
low processing power – in this case an assistive device for the visually impaired. Our platform of choice
here is the first generation Samsung Galaxy Gear smartwatch. Running solely in the watch, without pairing
to a phone or tablet, the system detects a face in the image captured by the camera, and then performs face
recognition (on a limited dictionary), emitting an audio feedback that either identifies the recognized person
or indicates that s/he is unknown. For the face recognition approach we use a variation of the K-NN
algorithm which accomplished the task with high accuracy rates. This paper presents the proposed system
and preliminary results on its evaluation.