Efficacy of AI Algorithms for Gesture Recognition in Android Apps
Keywords:
Gesture recognition, AI algorithms, Hand gesture identification, Dynamic gesturesAbstract
This research paper explores the efficacy of artificial intelligence (AI) algorithms for gesture recognition in Android applications. Gesture recognition plays a vital role in human-machine interaction, enabling intuitive communication and control in various applications. The study reviews existing literature on gesture recognition, outlines the research objectives, formulates hypotheses related to environmental factors and user-specific factors affecting gesture recognition accuracy, and presents the methodology used to evaluate AI techniques in the context of Android apps. The paper focuses on preprocessing and feature extraction techniques, presents results, and concludes by highlighting the significance of this research in bridging communication gaps and the potential for broader applications in human-machine interaction.
Downloads
References
Islam, S., Titli, S. R., Kabir, K. A., Al Hossain, M. A., & Hossain, M. A. (2022, June). Improving real-time hand gesture recognition system for translation: Sensor development. In 2022 17th Annual System of Systems Engineering Conference (SOSE): 254-259
Khan, Rafiqul Zaman and Noor Adnan Ibraheem (2012). Comparative Study of Hand Gesture Recognition System. Natarajan Meghanathan, et al. (Eds). Conference: International Conference of Advanced Computer Science & Information Technology: 203–213
Mohammed, H. I., Waleed, J., &Albawi, S. (2021).An Inclusive Survey of Machine Learning based Hand Gestures Recognition Systems in Recent Applications.IOP ConferenceSeries: MaterialsScience and Engineering, 1076(1), 012047
Neiva, D. H., & Zanchettin, C. (2018). Gesture recognition: A review focusing on sign language in a mobile context. Expert Systems with Applications, 103, 159-183.
Ojeda-Castelo, J. J., Capobianco-Uriarte, M. D. L. M., Piedra-Fernandez, J. A., & Ayala, R. (2022). A Survey on Intelligent Gesture Recognition Techniques. IEEE Access, 10, 87135-87156.
Omar Al-Jarrah & Faruq A. Al-Omari (2007) Improving Gesture Recognition In The Arabic Sign Language Using Texture Analysis, Applied Artificial Intelligence, 21:1, 11-33
Padmapriya, Dr. S., S. Vignesh and N. Siddharth (2015). Hand Gesture Recognition Using An Android. nternational Journal of Research in Science and Technology 2(1): 72-76
Rzecki, K. (2020). Classification algorithm for person identification and gesture recognition based on hand gestures with small training sets. Sensors, 20(24), 1–14.
Sharma, Ashish, Anmol Mittal, Savitoj Singh, Vasudev Awatramani (2020). Hand Gesture Recognition using Image Processing and Feature Extraction Techniques. International Conference on Smart Sustainable Intelligent Computing and Applications under ICITETM2020. Elsevier B.V
Siddiqui, N., &Chan, R. H. M. (2020). Multimodal hand gesture recognition using single IMU and acoustic measurements at wrist. PLOSONE, 15(1), e0227039
Yadav, A. (2021). How artificialintelligence is transforming the bankingindustry: Dataanalysisreview.International Journal of Advanced Research in Science, Communication and Technology, 76–81
Zheng, X., & Koenig, S. (2010). A project on gesture recognition with neural networks for ’introduction to artificial intelligence’classes. unpublished manual, University of Southern California.