References
- HISSAH, S. A. M. A. et al.: Detection of hand gestures with human computer recognition by using support vector machine, Periodicals of Engineering and Natural Sciences (PEN) 10, No. 2 (2022) 48–57 https://doi.org/10.21533/pen.v10i2.2866
- BEDDIAR, D. R. and NINI, B. and SABOKROU, M. and HADID, A.: Vision-based human activity recognition: a survey, Multimedia Tools and Applications 79, No. 41 (2020) 30509–30555 https://doi.org/10.1007/s11042-020-09004-3
- WANG, H. et al.: A systematic literature review of computer vision applications in robotized wire harness assembly, Advanced Engineering Informatics 59, No. (2024) 102596 https://doi.org/10.1016/j.aei.2024.102596
- PEREIRA, R. et al.: Systematic Review of Emotion Detection with Computer Vision and Deep Learning, Sensors 24, No. 11 (2024) 3484 https://doi.org/10.3390/s24113484
- LIU, L. et al.: Hand Gesture Recognition: A Review, IEEE Transactions on Human-Machine Systems 49, No. 4 (2019) 345–357 https://doi.org/10.1109/THMS.2019.2901659
- TIGRINI, A. et al.: Intelligent HumanâC“Computer Interaction: Combined Wrist and Forearm Myoelectric Signals for Handwriting Recognition, Bioengineering 11, No. 5 (2024) 458 https://doi.org/10.3390/bioengineering11050458
- AKDAG, A. and BAYKAN,Ă–. K.: Multi-Stream Isolated Sign Language Recognition Based on Finger Features Derived from Pose Data, Electronics 13, No. 8 (2024) 1591 https://doi.org/10.3390/electronics13081591
- YU, C. and GUAN, S.: Dynamic Gesture Tracking Recognition Based on TLD and DTW, Computer Systems Application 24, No. 10 (2015) 2–4
- ZHANG, J. and WANG, H. and LIU, Y. and JIANG, T. and WU, C.: Application of SVD and SVM Superposition Algorithm in Image Recognition of Glass Thermometer, Electronic Measurement Technology 38, No. 1 (2015) 1–3
- ZHANG, Y. et al.: 3D Hand Gesture Recognition Using a Convolutional Neural Network, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), No. (2017) 3111–3119 https://doi.org/10.1109/ICCVW.2017.369
- MITRA, S. and ACHARYA, T.: Gesture Recognition: A Survey, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 37, No. 3 (2007) 311–324 https://doi.org/10.1109/TSMCC.2007.893280
- YANG, H. et al.: Real-Time Hand Gesture Recognition Using Finger-Earth Mover’s Distance and Convolutional Neural Networks, IEEE Transactions on Industrial Informatics 15, No. 4 (2019) 1770–1779 https://doi.org/10.1109/TII.2018.2841423
- CHEN, Y. et al.: A Survey on Hand Gesture Recognition, IEEE Transactions on Systems, Man, and Cybernetics: Systems 48, No. 5 (2018) 744–758 https://doi.org/10.1109/TSMC.2018.2865940
- ESCALERA, S. et al.: Challenges in Multi-modal Gesture Recognition, Journal of Machine Learning Research 17, No. 48 (2016) 1–54
- WANG, M. and DU, Y. and ZHANG, Z.: Research on UAV-assisted inspection and image recognition of insulator defects, Journal of Electronic Measurement and Instrumentation 29, No. 12 (2015) 2–3
- DESHPANDE, J. S. P.: Hand Gesture Identification Using Deep Learning and Artificial Neural Networks: A Review, Lecture Notes in Electrical Engineering 825, No. (2023) 547–560 https://doi.org/10.1007/978-981-19-1754-2_40
- BANDINI, A. and ZARIFFA, J.: Analysis of the Hands in Egocentric Vision: A Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence 42, No. 10 (2020) 2530–2542 https://doi.org/10.1109/TPAMI.2019.2938134
- CHUNG, Y.-L. and CHUNG, H.-Y. and TSAI, W.-F.: Hand gesture recognition via image processing techniques and deep CNN, Journal of Intelligent & Fuzzy Systems 39, No. 2 (2020) 1719–1733 https://doi.org/10.3233/JIFS-179939
- XU, J. and LI, J. and ZHANG, S. and XIE, C. and DONG, J.: Skeleton guided conflict-free hand gesture recognition for robot control, 2020 International Conference on Advanced Robotics and Intelligent Systems (ARIS), No. (2020) 275–282 https://doi.org/10.1109/ARIS50974.2020.9205999
- HAN, M. and ZANDIGOHAR, M. and KIM, M.: Classifications of dynamic EMG in hand gesture and unsupervised grasp motion segmentation, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), No. (2021) 553–558 https://doi.org/10.1109/EMBC46164.2021.9630232
- ZHOU, Q. and XIE, G. and ZHANG, J. and WEI, Y.: Dynamic Hand Gesture Recognition with Adaptive HMM Based on Multi-feature Fusion, Journal of Computer Applications 38, No. 5 (2018) 1432–1438
- LUPINETTI, K. et al.: 3D Dynamic Hand Gestures Recognition Using the Leap Motion Sensor and Convolutional Neural Networks, Lecture Notes in Computer Science 12287, No. (2020) 464–471 https://doi.org/10.1007/978-3-030-58465-8_31
- ALNAIM, N. et al.: Recognition of Holoscopic 3D Video Hand Gesture Using Convolutional Neural Networks, Technologies 8, No. 2 (2020) 19 https://doi.org/10.3390/technologies8020019
- RIZWAN, M. et al.: Appearance Based Dynamic Hand Gesture Recognition Using 3D Separable Convolutional Neural Network, Computers, Materials & Continua 75, No. 1 (2023) 1–20 https://doi.org/10.32604/cmc.2023.038211
- GONZALEZ, R. C. Digital Image Processing. Pearson Education India, 2009.
- DE SMEDT, Q.; WANNOUS, H.; VANDEBORRE, J. P.; GUERRY, J.; LE SAUX, B.; FILLIAT, D. SHREC’16 track: 3D hand gesture recognition using a depth and skeletal dataset. In: Proceedings of the 9th Eurographics Workshop on 3D Object Retrieval. Eurographics Association, 2016. p. 85–93.