direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Page Content

Lupe

Sven Kratz is now with Ludwig-Maximilians-Universität München

Research Field


Human-Computer-Interaction (HCI)

Research Topics


- Novel sensor-based mobile interactions
- Mobile navigation of large information spaces
- Motion gesture recognition
- Physical and tangible user interfaces

Biography


Sven Kratz is a research assistant with Deutsche Telekom Laboratories at TU Berlin, where he is also currently pursuing his Phd studies. His primary research focus is on sensor-based mobile interfaces that allow for novel types of interaction. This includes gesture recognition, interaction based on distance sensing and pressure, tabletop applications for mobile devices and optical tracking technologies. Sven also conducts research into mobile interfaces providing efficient navigation of large information spaces such as maps, 3D environments or databases.

Sven received his Diplom degree in Computer Science from RWTH-Aachen University in 2008. In 2007, while working at the Media Computing Group at RWTH Aachen, Sven participated in the development, deployment and the user interface design of the mobile pervasive city game REXplorer, the first mobile city game released in public.

During his free time, Sven enjoys sailing, playing tennis and traveling the world.

Address


Quality and Usability Lab
Deutsche Telekom Laboratories
TU Berlin
Errnst-Reuter-Platz 7
D-10587 Berlin, Germany

Publications

Protractor3D: A Closed-Form Solution to Rotation-Invariant 3D Gestures
Citation key kratz2011a
Author Kratz, Sven and Rohs, Michael
Title of Book Proceedings of the 2011 International Conference on Intelligent User Interfaces (IUI 2011)
Year 2011
Location Palo Alto, California, USA
Month feb
Publisher ACM Press
Abstract Protractor 3D is a gesture recognizer that extends the 2D touch screen gesture recognizer Protractor to 3D gestures. It inherits many of Protractor's desirable properties, such as high recognition rate, low computational and low memory requirements, ease of implementation, ease of customization, and low number of required training samples. Protractor 3D is based on a closed-form solution to finding the optimal rotation angle between two gesture traces involving quaternions. It uses a nearest neighbor approach to classify input gestures. It is thus well-suited for application in resource-constrained mobile devices. We present the design of the algorithm and a study that evaluated its performance.
Link to original publication Download Bibtex entry

Zusatzinformationen / Extras

Quick Access:

Schnellnavigation zur Seite über Nummerneingabe