TY  - CONF
ID  - SisLab2647
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2647/
A1  - Ma Thi, Chau
A1  - Tabia, Karim
A1  - Sylvain, Lagrue
A1  - Nguyen, Thanh Thuy
A1  - Le, Thanh Ha
A1  - Bui, The Duy
Y1  - 2017/06//
N2  - This paper aims at the annotation of movement phrases in Vietnamese folk dance videos that were mainly gathered, stored and used in teaching at art schools and in preserving cultural intangible heritages (performed by different famous folk dance masters). We propose a framework of automatic movement phrase annotation, in which the motion vectors are used as movement phrase features. Movement phrase classification can be carried out, based on dancer?s trajectories. A deep investigation of Vietnamese folk dance gives an idea of using optical flow as movement phrase features in movement phrase detection and classification. For the richness and usefulness in annotation of Vietnamese folk dance, a lookup table of movement phrase descriptions is defined. In initial experiments, a sample movement phrase dataset is built up to train k-NN classification model. Experiments have shown the effectiveness of the proposed framework of automatic movement phrase annotation with classification accuracy at least 88%.
TI  - Annotating movement phrases in Vietnamese folk dance videos
SP  - 3
M2  - Arras, France
AV  - none
EP  - 11
T2  - International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2017: Advances in Artificial Intelligence: From Theory to Practice
ER  -