Objective of the project

• Image-based identification and classification of dance forms using AI and ML frameworks, based on costume signatures.

• To develop a Natyashastra and Abhinaya Darpana-based NrithyAI Chatbot

• To generate new postures not found in the already composed dance item and map it to the Jathi

Publication

[C3] S. Karthika, R. Srinivasan, Malavika. C.V, Nrithya: a Curated Image Dataset of Indian Folk and South Indian Classical Dance Forms, Selected for Oral presentation in IEEE TENCON 2025, Kota Kinabalu, Malaysia, October 2025 

[C2] S. Karthika, R. Srinivasan, Malavika. C.V, ‘Costumed Clues: Classifying South Indian Classical Dance’, Lecture Notes in Networks and Systems, Springer, 2025 (Scopus - in press)

[C1] Pavithra Manikandan, Aravind Vijayaraghavan, S. Karthika, R. Srinivasan, “Identification and Classification of Eye Movements in Bharatanatyam using Deep Learning Techniques”, 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023Volume: 2023-JunePages: 566 - 573, EID: 2-s2.0-85174239411 (Scopus) 

[BC1] Shriram, M.S., Sushmitha, S., Karthika, S. (2025). A Symphony of Movements: Deep Learning for Thattadavu Recognition in Bharatanatyam. In: Bansal, J.C., Sharma, H., Chakravorty, A. (eds) Congress on Smart Computing Technologies. CSCT 2022. Smart Innovation, Systems and Technologies, vol 396. Springer, Singapore. https://doi.org/10.1007/978-981-97-8096-9_9 (Scopus)

Thesis

[1] Aashish M & Harish K, Gestural Grammar: AI Vision for anthropology analysis, FYP Thesis, B.Tech IT (2021-2025)

[2] Nirranjana R & Aishwarya R, Understanding ethnochoreology using computational modelling, FYP Thesis, B.Tech IT (2021-2025)

Datasets

1. Pose detection in Karanas

2. Eye Movement Classification

3. Costume Clues: Classical Dance Forms

4. Costume Clues: Folk Dance Forms

5. Jatiswaram Classification

6. Padam Classification