Details

Autor(en) / Beteiligte

• Shanhe Yi
• Zhengrui Qin
• Novak, Ed
• Yafeng Yin
• Qun Li

Titel

GlassGesture: Exploring head gesture interface of smart glasses

Ist Teil von

• IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, 2016, p.1-9

Ort / Verlag

IEEE

Erscheinungsjahr

2016

Link zum Volltext

Quelle

IEEE Xplore (IEEE/IET Electronic Library - IEL)

Beschreibungen/Notizen

• We have seen an emerging trend towards wearables nowadays. In this paper, we focus on smart glasses, whose current interfaces are difficult to use, error-prone, and provide no or insecure user authentication. We thus present GlassGesture, a system that improves Google Glass through a gesture-based user interface, which provides efficient gesture recognition and robust authentication. First, our gesture recognition enables the use of simple head gestures as input. It is accurate in various wearer activities regardless of noise. Particularly, we improve the recognition efficiency significantly by employing a novel similarity search scheme. Second, our gesture-based authentication can identify owner through features extracted from head movements. We improve the authentication performance by proposing new features based on peak analyses, and employing an ensemble method. Last, we implement GlassGesture and present extensive evaluations. GlassGesture achieves a gesture recognition accuracy near 96%. For authentication, GlassGesture can accept authorized users in near 92% of trials, and reject attackers in near 99% of trials. We also show that in 100 trials imitators cannot successfully masquerade as the authorized user even once.