參考文獻 |
References
[1] G. Odowichuk, S. Trail, W. Page, W. Nie and P. Driessen, "Sensor fusion: Towards a fully expressive 3D music control interface," in Proceedings of 2011 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, Victoria, BC, Canada, 2011.
[2] L. S. Figueiredo, J. Teixeira, A. S. Cavalcanti, V. Teichrieb and J. Kelner, "An Open-Source Framework for Air Guitar Games," in VIII Brazilian Symposium on Games and Digital Entertainment, Rio de Janeiro, Brazil, 2009.
[3] Y. Che and Y. Qi, "Dynamic Projected Segmentation Networks For Hand Pose Estimation," in 2018 24th International Conference on Pattern Recognition (ICPR), Beijing, China, 2018.
[4] S. E. Wei, V. Ramakrishna, T. Kanade and Y. Sheikh, "Convolutional Pose Machines," in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 2016.
[5] C. Zimmermann and T. Brox, "Learning to Estimate 3D Hand Pose from Single RGB Images," in 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy, 2017.
[6] Y. Wang, C. Peng and Y. Liu, "Mask-Pose Cascaded CNN for 2D Hand Pose Estimation From Single Color Image," IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 11, pp. 3258-3268, 2018.
[7] S. Baek, K. I. Kim and T.-K. Kim, "Pushing the Envelope for RGB-Based Dense 3D Hand Pose Estimation via Neural Rendering," in 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA, USA, 2019.
[8] Y. Che, Y. Song and Y. Qi, "A Novel Framework of Hand Localization and Hand Pose Estimation," in ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom, United Kingdom, 2019.
[9] L. Ge, H. Liang, J. Yuan and D. Thalmann, "Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 4, pp. 956 - 970, 1 4 2019.
[10] C. R. Naguri and R. C. Bunescu, "Recognition of Dynamic Hand Gestures from 3D Motion Data using LSTM and CNN architectures," in 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA), Cancun, Mexico, 2018.
[11] R. Azad, M. Asadi-Aghbolaghi, S. Kasaei and S. Escalera, "Dynamic 3D Hand Gesture Recognition by Learning Weighted Depth Motion Maps," IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 6, pp. 1729 - 1740, 12 7 2018.
[12] Y.-J. Son and O. Choi, "Image-based hand pose classification using faster R-CNN," in 2017 17th International Conference on Control, Automation and Systems (ICCAS), Jeju, South Korea, 2017.
[13] M. Abavisani, H. R. Vaezi Joze and V. M. Patel, "Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition With Multimodal Training".
[14] F. Wang, L. Kong, X. Zhang and H. Chen, "Gesture Recognition and Localization Using Convolutional Neural Network," in 2019 Chinese Control And Decision Conference (CCDC), Nanchang, China, China.
[15] N. Dhingra and A. Kunz, "Res3ATN -Deep 3D Residual Attention Network for Hand Gesture Recognition in Videos," in 2019 International Conference on 3D Vision (3DV), Québec City, QC, Canada, Canada, 2019.
[16] O. Köpüklü, A. Gunduz, N. Kose and G. Rigoll, "Real-time Hand Gesture Detection and Classification Using Convolutional Neural Networks," in 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019), Lille, France, France, 2019.
[17] "MIDI - Wikipedia," Wikipedia, [Online]. Available: https://en.wikipedia.org/wiki/MIDI.
[18] C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke and A. Rabinovich, "Going deeper with convolutions," in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, 2015.
[19] K. He, X. Zhang, S. Ren and J. Sun, "Deep Residual Learning for Image Recognition," in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 2016. |