Single-hand Gesture Recognition of Manipuri Classical Dance of India based on Skeletonization Technique

Gesture recognition means recognizing of different expressions by which people can communicate with the outer world. Gestures recognition may be of verbal or non-verbal. In gesture recognition, hand gestures are one of the most common forms of communication, and they can communicate with a wide range of meanings. Dance gestures recognition is one of the challenging tasks in pattern recognition where hand gestures are used. It is a linguistic treatment of human motion through which one can depict dance drama and communicate culturally with people. This paper works with the Manipuri classical dance hand gestures which is among the eight Indian classical dances of India. In Manipuri classical dance, there are 25 single-hand gestures (Asamyukta Mudras) and 12 dual-hand gestures (Samyukta Mudras) are used. Unlike other Indian classical dance forms (eg: Bharatnatyam, Odissi, Kathak), there are no datasets available for Asamyukta mudras of Manipuri classical dance to continue the research work. So, the creation of the Manipuri single-hand gestures dataset is the main motivation behind this work. Here, for this dataset, 1500 mudras were collected from 6 volunteers from different angles of view. This paper also presents a study on various methods for gesture recognition with their applications. Finally, using skeletization technique, four features have been extracted to recognize 25 Asamyukta Mudras, and it can also be possible to identify whether the left or right hand is used to represent the Mudras.