TY - GEN
T1 - From Virtual to Real World
T2 - 2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI EA 2021
AU - Xia, Chengshuo
AU - Sugiura, Yuta
N1 - Funding Information:
This work was supported by JST PRESTO Grant Numbers JP-MJPR17J4 and JST AIP-PRISM Grant Numbers JPMJCR18Y2.
Publisher Copyright:
© 2021 ACM.
PY - 2021/5/8
Y1 - 2021/5/8
N2 - Following the conventional pipeline, the training dataset of a human activity recognition system relies on the detection of the significant signal variation regions. Such position-specific classifiers provide less flexibility for users to alter the sensor positions. In this paper, we proposed to employ the simulated sensor to generate the corresponding signal from human motion animation as the dataset. Visualizing the corresponding items from the real world, the user can determine the sensor's placement arbitrarily and obtain accuracy feedback as well as the classifier interface to get relief from the cost of a conventional training model. With the cases validation, the classifier trained by simulated sensor data can effectively recognize the real-world activity.
AB - Following the conventional pipeline, the training dataset of a human activity recognition system relies on the detection of the significant signal variation regions. Such position-specific classifiers provide less flexibility for users to alter the sensor positions. In this paper, we proposed to employ the simulated sensor to generate the corresponding signal from human motion animation as the dataset. Visualizing the corresponding items from the real world, the user can determine the sensor's placement arbitrarily and obtain accuracy feedback as well as the classifier interface to get relief from the cost of a conventional training model. With the cases validation, the classifier trained by simulated sensor data can effectively recognize the real-world activity.
KW - Activity recognition
KW - Machine learning
KW - Sensor simulation
UR - http://www.scopus.com/inward/record.url?scp=85105818681&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85105818681&partnerID=8YFLogxK
U2 - 10.1145/3411763.3451677
DO - 10.1145/3411763.3451677
M3 - Conference contribution
AN - SCOPUS:85105818681
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, CHI EA 2021
PB - Association for Computing Machinery
Y2 - 8 May 2021 through 13 May 2021
ER -