Research Project: Bakış Yönü Kullanabilen, Çizim Temelli Çok Kipli Akıllı İnsan-Bilgisayar Arayüzleri
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Contributors
Funders
ID
TB.00046
Authors
Sezgin, Tevfik Metin
Faculty Member
Publications
Gaze-based virtual task predictor
(Association for Computing Machinery, 2014) Çığ, Çağla; Sezgin, Tevfik Metin; Department of Computer Engineering; Graduate School of Sciences and Engineering; Yes; College of Engineering; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
Pen-based systems promise an intuitive and natural interaction paradigm for tablet PCs and stylus-enabled phones. However, typical pen-based interfaces require users to switch modes frequently in order to complete ordinary tasks. Mode switching is usually achieved through hard or soft modifier keys, buttons, and soft-menus. Frequent invocation of these auxiliary mode switching elements goes against the goal of intuitive, fluid, and natural interaction. In this paper, we present a gaze-based virtual task prediction system that has the potential to alleviate dependence on explicit mode switching in pen-based systems. In particular, we show that a range of virtual manipulation commands, that would otherwise require auxiliary mode switching elements, can be issued with an 80% success rate with the aid of users' natural eye gaze behavior during pen-only interaction.
Gaze-based proactive user interface for pen-based systems
(Association for Computing Machinery, 2014) Çığ, Çağla; Graduate School of Sciences and Engineering; No; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
In typical human-computer interaction, users convey their intentions through traditional input devices (e.g. keyboards, mice, joysticks) coupled with standard graphical user interface elements. Recently, pen-based interaction has emerged as a more intuitive alternative to these traditional means. However, existing pen-based systems are limited by the fact that they rely heavily on auxiliary mode switching mechanisms during interaction (e.g. hard or soft modifier keys, buttons, menus). In this paper, I describe the roadmap for my PhD research which aims at using eye gaze movements that naturally occur during pen-based interaction to reduce dependency on explicit mode selection mechanisms in pen-based systems.
