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AIST Dance Video Database: Multi-Genre, Multi-Dancer, and Multi-Camera Database for Dance Information Processing

  1. AIST Dance Video Database: Multi-Genre, Multi-Dancer, and Multi-Camera Database for Dance Information Processing Shuhei Tsuchida, Satoru Fukayama, Masahiro Hamasaki, Masataka Goto National Institute of Advanced Industrial Science and Technology (AIST)   ISMIR 2019
  2. AIST Dance Video Database: Multi-Genre, Multi-Dancer, and Multi-Camera Database for Dance Information Processing • Many researchers created 
 a variety of databases containing music • The fi rst large-scale shared database 
 focusing on street dances • Facilitate research on a variety of tasks 
 related to dancing to music
  3. Dance Information Processing
  4. Dance Information Processing •Dancer identi fi cation •Dance-technique estimation •Dance-motion genre classi fi cation •Structural analysis of choreographies •Dance-mood analysis •etc. Various types of processing and research related to dance information
  5. Why Dance? Dance Motion Dance Music •Dance motion is highly related to music • Clarify the relationship between motion and music • Useful for machine-learning purposes and 
 various benchmarks
  6. 1,618 street dances in 13,940 videos (multiple cameras) 60 musical pieces Database Structure
  7. Multiple Genres Dancers Cameras
  8. Multiple Genres Dancers Cameras Break, Pop, Lock, Waack, Middle hip-hop, LA-style hip-hop, House, Krump, Street Jazz, Ballet Jazz 10 major street dances
  9. Multiple Genres Dancers Cameras Solo and group dancing by 35 professional dancers
  10. Multiple Genres Dancers Cameras At most nine video cameras surrounding a dancer Front Right Back Left
  11. Multiple Genres Dancers Cameras
  12. Multiple genres dancers cameras Multiple Multiple ・New MIR tasks - Dancer identi fi cation - Dance-technique estimation - Dance-motion genre classi fi cation - etc. ・Various image processing tasks ・Investigate the relationship between motion and music
  13. Dance-Motion Genre-Classi fi cation Task Summary: LSTM-based model 0.67 sec: 56.6% 32.0 sec: 91.4 % Dataset: 210 videos shot from the front Task: Classifying 10 genres by using their video frames only 50 60 70 80 90 100 40 160 240 320 400 480 560 640 720 800 880 960 1120 1280 1600 Accuracy (%) Video frames Video ? Break Pop Lock Waack Krump House Middle hip-hop Street jazz
  14. https://aistdancedb.ongaaccel.jp FREE OF CHARGE