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Inference and machine learning methods in human-computer interaction

Objectif

My overall vision is that by combining inference algorithms and user interface technology, we can construct more human-computer interaction interfaces that are more efficient, less fatiguing and more interesting to use. In my dissertation I focused on using such an approach for effective text and command entry on mobile devices. In this proposal I want to widen the scope of my investigation from just mobile text entry interfaces to general gestural interfaces, with a special application for an effective end-user programming environment. My proposal can be subdivided into four research objectives whereas the first two will be tackled from day 1 while the fourth research objective will grow out of the research results from the first two. Immediate research objective 1: tapping vs. gesturing geometric patterns Immediate research objective 2: visualization of pen-gesture recognition Immediate research objective 3: tool support for the design of pen-gestures Research objective 4: sketch-based end-user programming environment Both pen-based and multi-touch interaction are increasingly gaining popularity among journalists and manufacturers with the arrival of the Apple iPhone and LG high-end mobile phones with their advanced touch-screens. Large multi-touch sensitive displays and pen-based tablet computers are becoming commodity electronic equipment, no longer reserved for research labs. At the same time, processing power and memory on both desktop and mobile devices have improved to allow smarter algorithms to be implemented. This project will provide new innovations and research insights that make these types of devices more practical and more attractive for consumers and professionals. Several European companies could benefit from this research being pursued from within Europe, for example Sony Ericsson and Nokia. My intention is to seek a faculty position at a European university after the fellowship and start a research group in this research area.

Appel à propositions

FP7-PEOPLE-2007-2-1-IEF
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Coordinateur

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Contribution de l’UE
€ 161 225,98
Adresse
TRINITY LANE THE OLD SCHOOLS
CB2 1TN Cambridge
Royaume-Uni

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Région
East of England East Anglia Cambridgeshire CC
Type d’activité
Higher or Secondary Education Establishments
Contact administratif
Dawn Barker (Ms.)
Liens
Coût total
Aucune donnée