The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Fusion of Inertial and Depth Sensor Data for Robust Hand Gesture Recognition
Abstract
This paper presents the first attempt at fusing data from inertial and vision depth sensors within the framework of a hidden Markov model for the application of hand gesture recognition. The data fusion approach introduced in this paper is general purpose in the sense that it can be used for recognition of various body movements. It is shown that the fusion of data from the vision depth and inertial sensors act in a complementary manner leading to a more robust recognition outcome compared with the situations when each sensor is used individually on its own. The obtained recognition rates for the single hand gestures in the Microsoft MSR data set indicate that our fusion approach provides improved recognition in real-time and under realistic conditions.
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Citations
Cites
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
Real time hand pose estimation using depth sensors
Keskin, C., Kirac, F., Kara, Y. E., & Akarun, L. (2011) · 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops) · doi:10.1109/iccvw.2011.6130391 · Cited by 190
Cited by
A survey on wearable sensor modality centred human activity recognition in health care
Wang, Y., Cang, S., & Yu, H. (2019) · Expert Systems with Applications · doi:10.1016/j.eswa.2019.04.057 · Cited by 409
A survey of depth and inertial sensor fusion for human action recognition
Chen, C., Jafari, R., & Kehtarnavaz, N. (2017) · Multimedia Tools and Applications · doi:10.1007/s11042-015-3177-1 · Cited by 356
Self-citationWearable Inertial Sensors for Human Motion Analysis: A Review
Lopez-Nava, I. H., & Munoz-Melendez, A. (2016) · IEEE Sensors Journal · doi:10.1109/jsen.2016.2609392 · Cited by 263
Deep Fisher discriminant learning for mobile hand gesture recognition
Li, C., Xie, C., Zhang, B., Chen, C., & Han, J. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2017.12.023 · Cited by 72
Self-citationFusion of Wearable and Contactless Sensors for Intelligent Gesture Recognition
Liang, X., Li, H., Wang, W., Liu, Y., Ghannam, R., Fioranelli, F., & Heidari, H. (2019) · Advanced Intelligent Systems · doi:10.1002/aisy.201900088 · Cited by 64
Metadata
- Authors
- Liu, K., Chen, C., Jafari, R., & Kehtarnavaz, N.
- Venue
- IEEE Sensors Journal
- Published
- 2014-06
- Volume
- 14
- Issue
- 6
- Pages
- 1898-1903
- ISSN
- 1530-437X (ISSN-L)
- 1558-1748
- OpenAlex
- W2046140781
- Cited by
- 163
- References
- 2
- FWCI
- 32.81
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liu, K., Chen, C., Jafari, R., & Kehtarnavaz, N. (2014). Fusion of Inertial and Depth Sensor Data for Robust Hand Gesture Recognition. IEEE Sensors Journal. https://doi.org/10.1109/jsen.2014.2306094
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