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@article{154134,
        author = {V . Janaranjani and N. Megala and R.Naveeth Kumar},
        title = {Hand Gesture Recognition For Dance Movements},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {10},
        pages = {176-179},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154134},
        abstract = {This paper involves recognition of hand gestures using flex sensors. It consists of PIC16F877A microcontroller chip, to process the digital signals. The sensors are fixed in position inside a fabric glove which is worn by the user. The movements of the finger digits produce electrical signal which are conditioned, processed and displayed in PC. The template of gestures are stored in the PC as a database. The database stores five different gestures for a single person. These gestures form the basic mudras for a prominent classical dance form of India. Inputs from any person/same person fed from the sensors embedded on the glove is processed and compared with the templates already stored in the database. A match between the two gestures is identified and an output information “Match Identified” or “not matched” is displayed in the PC. This helps to teach/learn basic mudras with the help of a hand gesture recognition system. This can also be implemented as a Dance Learning App in an ANDROID mobile.},
        keywords = {gesture recognition, flex sensor, Basic mudras, data base, dance learning.},
        month = {},
        }