Walk-through the OPPORTUNITY dataset for activity recognition in sensor rich environments

Daniel Roggen, Alberto Calatroni, Mirco Rossi, Thomas Holleczek, Kilian Förster, Gerhard Tröster, Paul Lukowicz, David Bannach, Gerald Pirkl, Florian Wagner, Alois Ferscha, Jakob Doppler, Clemens Holzmann, Marc Kurz, Gerald Holl, Ricardo Chavarriaga, Marco Creatura, Jose Millan

Research output: Chapter in Book/Report/Conference proceedingsConference contribution


We aim at activity and context recognition in opportunistic sensor setups. The system ought to make use of sensor modalities that just happen to be available, rather than to rely on specic sensor deployment. In order to assess opportunistic activity recognition methods, we collected a large-scale dataset of complex activities in a highly sensor rich environment, with 72 sensors of 10 modalities in the environment, in objects and on-body. The dataset contains composite and atomic activities in large numbers (>28000 hand interactions). We present the activity scenario and the sensor setup. We show the user's activities and the corresponding sensor signals side by side. We argue that such a visualization may be an efficient form of dataset documentation, especially when such a dataset is shared, as it gives an insight into the complexity of the activities and richness of the sensor setup.
Original languageEnglish
Title of host publicationAdjunct Proceedings of the 8th International Conference on Pervasive Computing (Pervasive 2010), Video Paper
Publication statusPublished - 2010
Event8th International Conference on Pervasive Computing (Pervasive 2010) - Helsinki, Finland
Duration: 17 May 201020 May 2010


Conference8th International Conference on Pervasive Computing (Pervasive 2010)


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