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abstract

7th international workshop on human activity sensing corpus and applications (HASCA)

Published: 09 September 2019 Publication History

Abstract

The recognition of complex and subtle human behaviors from wearable sensors will enable next-generation human-oriented computing in scenarios of high societal value (e.g., dementia care). This will require large-scale human activity corpuses and much improved methods to recognize activities and the context in which they occur. This workshop deals with the challenges of designing reproducible experimental setups, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating systems in the real world. We wish to reflect on future methods, such as lifelong learning approaches that allow open-ended activity recognition. This year HASCA will welcome papers from participants to the Second Sussex-Huawei Locomotion and Transportation Recognition Competition and Open Lab Nursing Activity Recognition Challenge in special sessions.

References

[1]
2019. The University of Sussex-Huawei Locomotion (SHL) Dataset and Competition. http://www.shl-dataset.org/activity-recognition-challenge-2019/
[2]
H. Gjoreski, M. Ciliberto, L. Wang, F.J.O. Morales, S. Mekki, S. Valentin, and D. Roggen. 2018. The University of Sussex-Huawei Locomotion and Transportation Dataset for Multimodal Analytics with Mobile Devices. IEEE Access 6 (July 2018), 42592--42604.
[3]
N. Kawaguchi, Y. Yang, T. Yang, N. Ogawa, Y. Iwasaki, K. Kaji, T. Terada, K. Murao, S. Inoue, Y. Kawahara, Y. Sumi, and N. Nishio. 2011. HASC2011Corpus: Towards the Common Ground of Human Activity Recognition. In Proceedings of the 13th International Conference on Ubiquitous Computing (UbiComp '11). ACM, New York, NY, USA, 571--572.
[4]
D. Roggen, A. Calatroni, M. Rossi, T. Holleczek, G. Tröster, P. Lukowicz, G. Pirkl, D. Bannach, A. Ferscha, J. Doppler, C. Holzmann, M. Kurz, G. Holl, R. Chavarriaga, H. Sagha, H. Bayati, and J. del R. Millán. 2010. Collecting Complex Activity Data Sets in Highly Rich Networked Sensor Environments. In Proceedings of the Seventh International Conference on Networked Sensing Systems (INSS '10). IEEE.
[5]
L. Wang, H. Gjoreski, M. Ciliberto, S. Mekki, S. Valentin, and D. Roggen. 2019. Enabling Reproducible Research in Sensor-based Transportation Mode Recognition with the Sussex-Huawei Dataset. IEEE Access 7 (Jan. 2019), 10870--10891.

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cover image ACM Conferences
UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
September 2019
1234 pages
ISBN:9781450368698
DOI:10.1145/3341162
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Association for Computing Machinery

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Published: 09 September 2019

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Author Tags

  1. SHL activity recognition challenge
  2. activity recognition
  3. large scale human activity sensing corpus
  4. mobile sensors
  5. open lab nursing activity recognition challenge
  6. open-ended activity/context recognition
  7. participatory sensing
  8. smartphones
  9. wearable computing

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