Creating Database for Traditional Dance Categorization using CSV File Format

Abstract

Categorizing dance requires an enormous amount of data storage which usually uses video as storage file. Joint position values from body movement mainly become base in categorizing dance. Author proposes an offline database system for traditional dance categorization system which utilizes CSV file format storing those numerical values. The method provides an easily accessible and sufficient database system that serves as training dataset and avatar reconstruction data. Meanwhile, the dance categorization system utilizes hidden Markov model. Recorded file consumes 40% less storage space compared to Brekel Pro Body v2 CSV outputs and differentiates two sequence correctly.