Dr. Muhammad Zeshan Afzal

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Mhd Rashed Al Koutayni

Jilliam Maria Diaz Barros

Iuliia Brishtel

Mahdi Chamseddine

Steve Dias da Cruz

Ahmet Firintepe

Sophie Folawiyo

David Michael Fürst

Kamalveerkaur Garewal

Christiano Couto Gava

Leif Eric Goebel

Tewodros Amberbir Habtegebrial

Jigyasa Singh Katrolia

Andreas Kölsch

Onorina Kovalenko

Muhammad Jameel Nawaz Malik

Nareg Minaskan Karabid

Mohammad Minouei

Manthan Pancholi

Engr. Kumail Raza

Dr. Nadia Robertini

María Alejandra Sánchez Marín

Dr. Kripasindhu Sarkar

Alexander Schäfer

Pascal Schneider

Lukas Stefan Staecker

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão

Automatic Detection of Modes in Human Computer Interaction

Automatic Detection of Modes in Human Computer Interaction
Markus Weber
PhD Thesis

Abstract:: Most user interfaces have multiple interpretations of a given gesture. For example the usage of a console application, at one moment, tapping “Return” on a keyboard inserts a return character into the text, whereas at another time, tapping Return causes the text typed immediately prior to that tap to be executed as a command. Modes manifest how an interface responds to gestures. For any given gesture, the interface is in a particular mode if the interpretation of that gesture is constant. When that gesture has a different interpretation, the interface is in a different mode. This thesis addresses the issue of mode detection for various different input modalities. An automatic detection of the current mode will help to improve the usability in several applications. These techniques will help to improve the usability in applications, based on this kind of input methods.

Keywords:: Mode detection, automatic detection of modes, gesture interpretation

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