K. Kunze

Publications
Influence

In the blink of an eye: combining head motion and eye blink frequency for activity recognition with Google Glass

Shoya Ishimaru, K. Kunze, +4 authors Andreas Bulling
Computer Science
AH
7 March 2014

We demonstrate how information about eye blink frequency and head motion patterns derived from Google Glass sensors can be used to distinguish different types of high level activities. Expand

Symbolic Object Localization Through Active Sampling of Acceleration and Sound Signatures

K. Kunze, P. Lukowicz
Computer Science, Engineering
UbiComp
16 September 2007

We describe a novel method for symbolic location discovery of simple objects that uses vibration and short, narrow frequency 'beeps' to sample the response of the environment to mechanical stimuli. Expand

Where am I: Recognizing On-body Positions of Wearable Sensors

K. Kunze, P. Lukowicz, H. Junker, G. Tröster
Computer Science
LoCA
12 May 2005

The paper describes a method that allows us to derive the location of an acceleration sensor placed on the user's body solely based on the sensor's signal. Expand

Dealing with sensor displacement in motion-based onbody activity recognition systems

K. Kunze, P. Lukowicz
Computer Science
UbiComp
21 September 2008

We present a set of heuristics that significantly increase the robustness of motion sensor-based activity recognition with respect to sensor displacement. Expand

Using Wearable Sensors for Real-Time Recognition Tasks in Games of Martial Arts - An Initial Experiment

E. A. Heinz, K. Kunze, Matthias Gruber, D. Bannach, P. Lukowicz
Computer Science
IEEE Symposium on Computational Intelligence and…
22 May 2006

Beside their stunning graphics, modern entertainment systems feature ever-higher levels of immersive user-interaction. Expand

Using acceleration signatures from everyday activities for on-body device location

K. Kunze, P. Lukowicz
Computer Science
11th IEEE International Symposium on Wearable…
11 October 2007

This paper is part of an effort to facilitate wearable activity recognition using dynamically changing sets of sensors integrated in everyday appliances such as phones, PDAs, watches, headsets etc. Expand

Sensor Placement Variations in Wearable Activity Recognition

K. Kunze, P. Lukowicz
Computer Science
IEEE Pervasive Computing
1 October 2014

This article explores how placement variations in user-carried electronic appliances influence human action recognition and how such influence can be mitigated. Expand

Which Way Am I Facing: Inferring Horizontal Device Orientation from an Accelerometer Signal

K. Kunze, P. Lukowicz, K. Partridge, J. Begole
Computer Science
International Symposium on Wearable Computers
4 September 2009

We present a method to infer the orientation of mobile device carried in a pocket from the acceleration signal acquired when the user is walking. Expand

Facial Expression Recognition in Daily Life by Embedded Photo Reflective Sensors on Smart Eyewear

Katsutoshi Masai, Y. Sugiura, Masa Ogata, K. Kunze, M. Inami, M. Sugimoto
Computer Science
IUI
7 March 2016

This paper presents a novel smart eyewear that uses embedded photo reflective sensors and machine learning to recognize a wearer's facial expressions in daily life. Expand

Smarter eyewear: using commercial EOG glasses for activity recognition

Shoya Ishimaru, Yuji Uema, K. Kunze, K. Kise, Katsuma Tanaka, M. Inami
Computer Science
UbiComp Adjunct
13 September 2014

We present a first evaluation of soon commercially available Electrooculography (EOG) glasses (J!NS MEME) for the use in activity recognition. Expand

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