Research Article
Gesture Recognition: Translating Hand Symbols into Meaningful Names
@INPROCEEDINGS{10.4108/eai.28-4-2025.2358117, author={Sujitha Chintalapudi and Karri Vasundhara and Sarayu Potnuru and Bhagyasri Raja Rajeswari Devi Sandanala and Adiraju Raj Narayan Kaushik and B.C.S.N. Murthy Nukala}, title={Gesture Recognition: Translating Hand Symbols into Meaningful Names}, proceedings={Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part II}, publisher={EAI}, proceedings_a={ICITSM PART II}, year={2025}, month={10}, keywords={gesture recognition cnn lstm hybrid model cross-communication hearing impaired real-time adaptation hand symbols}, doi={10.4108/eai.28-4-2025.2358117} }- Sujitha Chintalapudi
Karri Vasundhara
Sarayu Potnuru
Bhagyasri Raja Rajeswari Devi Sandanala
Adiraju Raj Narayan Kaushik
B.C.S.N. Murthy Nukala
Year: 2025
Gesture Recognition: Translating Hand Symbols into Meaningful Names
ICITSM PART II
EAI
DOI: 10.4108/eai.28-4-2025.2358117
Abstract
This paper introduces a novel approach to gesture recognition tailored to empower individuals with hearing impairments. Leveraging a hybrid CNN+LSTM architecture, our model learns directly from user-provided gestures, bypassing the need for pre-existing datasets and enabling real-time adaptation. Through comprehensive experiments, we demonstrate the efficacy of our approach in accurately translating hand symbols into meaningful names. Our findings underscore the potential of personalized gesture recognition systems in fostering accessible and intuitive communication for the hearing impaired.
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