Utilizing Attention for Continuous Human Action Recognition Based on Multimodal Fusion of Visual and Inertial
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-57919-6_5
Reference15 articles.
1. Sun, Z., Ke, Q., Rahmani, H., Bennamoun, M., Wang, G., Liu, J.: Human action recognition from various data modalities: a review. IEEE Trans. Pattern Anal. Mach. Intell. 45(3), 3200–3225 (2022)
2. Dawar, N., Kehtarnavaz, N.: Real-time continuous detection and recognition of subject-specific smart tv gestures via fusion of depth and inertial sensing. IEEE Access 6, 7019–7028 (2018)
3. Majumder, S., Kehtarnavaz, N.: Vision and inertial sensing fusion for human action recognition: a review. IEEE Sens. J. 21(3), 2454–2467 (2020)
4. Li, T., Yu, H.: Visual - inertial fusion based human pose estimation: a review. IEEE Trans. Instrum. Meas. 72, 1–16 (2023)
5. Diete, A., Sztyler, T., Stuckenschmidt, H.: Vision and acceleration modalities: Partners for recognizing complex activities. In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 101–106. IEEE (2019)
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