HASC2011corpus: towards the common ground of human activity recognition

Authors:
Nobuo Kawaguchi;Ying Yang;Tianhui Yang;Nobuhiro Ogawa;Yohei Iwasaki;Katsuhiko Kaji;Tsutomu Terada;Kazuya Murao;Sozo Inoue;Yoshihiro Kawahara;Yasuyuki Sumi;Nobuhiko Nishio
Affiliations:
Nagoya University, Nagoya, Japan;Nagoya University, Nagoya, Japan;Nagoya University, Nagoya, Japan;Nagoya University, Nagoya, Japan;Nagoya University, Nagoya, Japan;Nagoya University, Nagoya, Japan;Kobe University, Kobe, Japan;Kobe University, Kobe, Japan;Kyushu Institute of Technology, Fukuoka, Japan;The University of Tokyo, Tokyo, Japan;Future University Hakodate, Hakodate, Japan;Ritsumeikan University, Kusatsu, Japan
Venue:
Proceedings of the 13th international conference on Ubiquitous computing
Year:
2011

Citing 2
Cited 2

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Proceedings of the 2nd Augmented Human International Conference
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ISWC '11 Proceedings of the 2011 15th Annual International Symposium on Wearable Computers

HASC-IPSC: indoor pedestrian sensing corpus with a balance of gender and age for indoor positioning and floor-plan generation researches

Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Chairs' summary/proposal for international workshop on human activity sensing corpus and its application (hasca2013)

Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication

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Abstract

Human activity recognition through the wearable sensor will enable a next-generation human-oriented ubiquitous computing. However, most of research on human activity recognition so far is based on small number of subjects, and non-public data. To overcome the situation, we have gathered 4897 accelerometer data with 116 subjects and compose them as HASC2011corpus. In the field of pattern recognition, it is very important to evaluate and to improve the recognition methods by using the same dataset as a common ground. We make the HASC2011corpus into public for the research community to use it as a common ground of the Human Activity Recognition. We also show several facts and results of obtained from the corpus.