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A Real-Time Human Action Recognition System Using Depth and Inertial Sensor Fusion
Abstract
This paper presents a human action recognition system that runs in real time and simultaneously uses a depth camera and an inertial sensor based on a previously developed sensor fusion method. Computationally efficient depth image features and inertial signals features are fed into two computationally efficient collaborative representative classifiers. A decision-level fusion is then performed. The developed real-time system is evaluated using a publicly available multimodal human action recognition data set by considering a comprehensive set of human actions. The overall classification rate of the developed real-time system is shown to be >97%, which is at least 9% higher than when each sensing modality is used individually. The results from both offline and real-time experimentations demonstrate the effectiveness of the system and its real-time throughputs.
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Cited by
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Chen, C., Jafari, R., & Kehtarnavaz, N. (2017) · Multimedia Tools and Applications · doi:10.1007/s11042-015-3177-1 · Cited by 356
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Alshehri, F., & Muhammad, G. (2021) · IEEE Access · doi:10.1109/access.2020.3047960 · Cited by 348
A comprehensive survey on multimodal medical signals fusion for smart healthcare systems
Muhammad, G., Alshehri, F., Karray, F., Saddik, A. E., Alsulaiman, M., & Falk, T. H. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.06.007 · Cited by 287
Metadata
- Authors
- Chen, C., Jafari, R., & Kehtarnavaz, N.
- Venue
- IEEE Sensors Journal
- Published
- 2016-02
- Volume
- 16
- Issue
- 3
- Pages
- 773-781
- ISSN
- 1530-437X (ISSN-L)
- 1558-1748
- 2379-9153
- OpenAlex
- W2246021102
- Cited by
- 187
- References
- 0
- FWCI
- 16.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Real-Time Human Action Recognition System Using Depth and Inertial Sensor Fusion. https://app.cochat.ai/papers/10.1109/jsen.2015.2487358
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- Chen, C., Jafari, R., & Kehtarnavaz, N. (2016). A Real-Time Human Action Recognition System Using Depth and Inertial Sensor Fusion. IEEE Sensors Journal. https://doi.org/10.1109/jsen.2015.2487358
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