Recording a complex, multi modal activity data set for context recogntion

23th International Conference on Architecture of Computing Systems 2010, ARCS 2010 - Workshop Proceedings

Volumn , Issue , 2010, Pages 161-166

  Lukowicz, P ^a   Pirkl, G ^a   Bannach, D ^a   Wagner, F ^a   Calatroni, A ^b   Forster K ^b   Holleczek, T ^b   Rossi, M ^b   Roggen, D ^b   Troester, G ^b   Doppler, J ^c   Holzmann, C ^c   Riener, A ^c   Ferscha, A ^c   Chavarriaga, R ^d  

^a UNIVERSITY OF PASSAU   (Germany)

^b SWISS FEDERAL INSTITUTE OF TECHNOLOGY   (Switzerland)

^c JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

^d EPFL   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

MOTION SENSORS;

DATA SET; IN CONTEXTS; MULTI-MODAL; MULTIMODAL SENSOR; PICKING UP; RESEARCH QUESTIONS; RESEARCH TOOLS; SOUND SOURCE;

COMPUTER ARCHITECTURE;

EID: 85018097961     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Intille, S., Larson, K., Tapia, E., Beaudin, J., Kaushik, P., Nawyn, J., Rockinson, R.: Using a live-in laboratory for ubiquitous computing research. (2006) 349-365
2. Tenorth, M., Bandouch, J., Beetz, M.: The TUM kitchen data set of everyday manipulation activities for motion tracking and action recognition. In: IEEE Int. Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences (THEMIS). In conjunction with ICCV2009. (2009)
3. van Kasteren, T., Noulas, A., Englebienne, G., Kröse, B.: Accurate activity recognition in a home setting. In: UbiComp'08: Proceedings of the 10th international conference on Ubiquitous computing, New York, NY, USA, ACM (2008) 1-9
4. Wu, J., Osuntogun, A., Choudhury, T., Philipose, M., Rehg, J.: A scalable approach to activity recognition based on object use. In: Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on. (Oct. 2007) 1-8
5. Wilson, D.H., Atkeson, C.: Simultaneous tracking and activity recognition (star) using many anonymous, binary sensors. In: Pervasive Computing. (2005) 62-79
6. Kranz, M., Schmidt, A., Maldonado, A., Rusu, R.B., Beetz, M., Hoernler, B., Rigoll, G.: Context-aware kitchen utilities. In: TEI'07: Proceedings of the 1st international conference on Tangible and embedded interaction, New York, NY, USA, ACM Press (2007) 213-214
7. Tenorth, M., Bandouch, J., Beetz, M.: The TUM kitchen data set of everyday manipulation activities for motion tracking and action recognition. In: IEEE Int. Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences (THEMIS). In conjunction with ICCV2009. (2009)
8. Stiefmeier, T., Roggen, D., Ogris, G., Lukowicz, P., Tröster, G.: Wearable activity tracking in car manufacturing. IEEE Pervasive Computing 7(2) (2008) 42-50
9. Pirkl, G., Stockinger, K., Kunze, K., Lukowicz, P.: Adapting magnetic resonant coupling based relative positioning technology for wearable activitiy recogniton. Twelfth IEEE International Symposium on Wearable Computers (ISWC 2008) (2007) 47 - 54
10. Bächlin, M., Roggen, D., Tröster, G.: Context-aware platform for long-term life style management and medical signal analysis. In: Proceedings of the 2nd SENSATION International Conference. (0 2007)
11. Bauer, G., Stockinger, K., Lukowicz, P.: Recognizing the use-mode of kitchen appliances from their current consumption. In: Smart Sensing and Context, EUROSSC09. (2009) 163-176
12. Bauer, G., Lukowicz, P.: Developing a sub room level indoor location system for wide scale deployment in assisted living systems. In: Proc. 11th Int. Conf. on Computers Helping People with Special Needs, Springer LNCS (2008)