Creating Database for Traditional Dance Categorization using CSV File Format
| Autor: | Khairurizal Alfathdyanto, Ary Setijadi Prihatmanto, Maria Shusanti Febrianti, Carmadi Machbub |
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| Rok vydání: | 2018 |
| Předmět: |
Database
Dance business.industry Computer science 05 social sciences 0507 social and economic geography Body movement 02 engineering and technology File format computer.software_genre Categorization Computer data storage 0202 electrical engineering electronic engineering information engineering Microsoft Windows 020201 artificial intelligence & image processing Joint (audio engineering) business Hidden Markov model 050703 geography computer |
| Zdroj: | 2018 IEEE 8th International Conference on System Engineering and Technology (ICSET). |
| DOI: | 10.1109/icsengt.2018.8606387 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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