A dynamic time warping approach to real-time activity recognition for food preparation

Cuong Pham, Thomas Plötz, Patrick Olivier

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

23 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationAmbient Intelligence - First International Joint Conference, AmI 2010, Proceedings
Number of pages10
Publication statusPublished - 3 Dec 2010
Externally publishedYes
Event1st International Joint Conference on Ambient Intelligence, AmI 2010 - Malaga, Spain
Duration: 10 Nov 201012 Nov 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6439 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference1st International Joint Conference on Ambient Intelligence, AmI 2010

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