Activity and Context Recognition with Opportunistic Sensor Configurations

Opportunity Dataset - Publications

The following is a (non-exhaustive) list of publications that exploit the Opportunity dataset:

  • J. Gomes, et al. Mobile activity recognition
    using ubiquitous data stream mining
    . In: 14th International Conference on Data Warehousing
    and Knowledge Discovery - DaWaK, 2012.
  • M. Kurz et al. The OPPORTUNITY Framework and Data Processing Ecosystem for Opportunistic Activity and Context Recognition, Int J Sensors, Wireless Communications and Control, 2011.
  • R. Chavarriaga et al. Ensemble creation and reconfiguration for activity recognition: An information theoretic approach. IEEE Conf Systems, Man, and Cybernetics (SMC), 2011
  • G. Hölzl at al. A Framework for Opportunistic Context and Activity Recognition. 9th International Conference on Pervasive Computing (Pervasive2011),  2011.
  • H. Sagha et al. Detecting anomalies to improve classification performance in an opportunistic sensor network, 7th IEEE International Workshop on Sensor Networks and Systems for Pervasive Computing (PerSens), 2011.
  • A. Calatroni et al., Automatic transfer of activity recognition capabilities between body-worn motion sensors: Training newcomers to recognize locomotion, 8th International Conference on Networked Sensing Systems (INSS), 2011
  • M. Kurz et al. Dynamic Quantification of Activity Recognition Capabilities in Opportunistic Systems. Fourth Conference on Context Awareness for Proactive Systems, 2011
  • H. Sagha et al. Detecting and rectifying anomalies in Opportunistic sensor networks. International Conference on Body Sensor Networks (BSN), 2011
  • A. Manzoor et al., Identifying Important Action Primitives for High Level Activity Recognition, Proc. European Conference on Smart Sensing and Context (EuroSSC), 2010
  • R. Chavarriaga et al. Robust activity recognition for assistive technologies: Benchmarking ML techniques, Workshop on Machine Learning for Assistive Technologies at the 24th Annual Conference on Neural Information Processing Systems (NIPS), 2010.
  • D. Roggen et al. Walk-through the OPPORTUNITY dataset for activity recognition in sensor rich environments, Adjunct Proceedings of the Eighth International Conference on Pervasive Computing, 2010
  • P. Lukowicz et al. Recording a complex, multi modal activity data set for context recognition 1st Workshop on Context-Systems Design, Evaluation and Optimisation at ARCS, 2010, 2010
  • D. Roggen et al. Collecting complex activity data sets in highly rich networked sensor environments, Proc. 7th Int Conf on Networked Sensing Systems (INSS), IEEE Computer Society Press, 2010.



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We develop opportunistic activity recognition systems: goal-oriented sensor assemblies spontaneously arise and self-organize to achieve a common activity and context recognition. We develop algorithms and architectures underlying context recognition in opportunistic systems.


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