Browse by author
Lookup NU author(s): Cuong Pham,
Dr Thomas Ploetz,
Professor Patrick OlivierORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
We present a dynamic time warping based activity recognition system for the analysis of low-level food preparation activities. Accelerometers embedded into kitchen utensils provide continuous sensor data streams while people are using them for cooking. The recognition framework analyzes frames of contiguous sensor readings in real-time with low latency. It thereby adapts to the idiosyncrasies of utensil use by automatically maintaining a template database. We demonstrate the effectiveness of the classification approach by a number of real-world practical experiments on a publically available dataset. The adaptive system shows superior performance compared to a static recognizer. Furthermore, we demonstrate the generalization capabilities of the system by gradually reducing the amount of training samples. The system achieves excellent classification results even if only a small number of training samples is available, which is especially relevant for real-world scenarios.
Author(s): Pham C, Plotz T, Olivier P
Editor(s): de Ruyter, B., Wichert, R., Keyson, D.V., Markopoulos, P., Streitz, N., Divitini, M., Georgantas, N., Mana Gomez, A.
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Ambient Intelligence: 1st International Joint Conference
Year of Conference: 2010
ISSN: 0302-9743 (print) 1611-3349 (online)
Library holdings: Search Newcastle University Library for this item
Series Title: Lecture Notes in Computer Science