Framework to Computationally Analyze Kathakali Videos

Bulani, Pratikkumar; S, Jayachandran; Sivaprasad, Sarath; Gandhi, Vineet

Framework to Computationally Analyze Kathakali Videos

Files

029-036.pdf (8.56 MB)

Date

2022

Authors

Bulani, Pratikkumar
S, Jayachandran
Sivaprasad, Sarath
Gandhi, Vineet

Publisher

The Eurographics Association

Abstract

Kathakali is one of the major forms of Classical Indian Dance. The dance form is distinguished by the elaborately colourful makeup, costumes and face masks. In this work, we present (a) a framework to analyze the facial expressions of the actors and (b) novel visualization techniques for the same. Due to extensive makeup, costumes and masks, the general face analysis techniques fail on Kathakali videos. We present a dataset with manually annotated Kathakali sequences for four downstream tasks, i.e. face detection, background subtraction, landmark detection and face segmentation. We rely on transfer learning and fine-tune deep learning models and present qualitative and quantitative results for these tasks. Finally, we present a novel application of style-transfer of Kathakali video onto a cartoonized face. The comprehensive framework presented in the paper paves the way for better understanding, analysis, pedagogy and visualization of Kathakali videos.

CCS Concepts: Applied computing --> Performing arts; Human-centered computing --> Visualization

        @inproceedings{10.2312:wiced.20221049
,
booktitle = {Workshop on Intelligent Cinematography and Editing
},
editor = {Ronfard, Rémi and 
Wu, Hui-Yin
},
title = {{Framework to Computationally Analyze Kathakali Videos
}},
author = {Bulani, Pratikkumar and 
S, Jayachandran and 
Sivaprasad, Sarath and 
Gandhi, Vineet
},
year = {2022
},
publisher = {The Eurographics Association
},
ISSN = {2411-9733
},
ISBN = {978-3-03868-173-1
},
DOI = {10.2312/wiced.20221049
}
}