TY - GEN
T1 - Visual Background Recommendation for Dance Performances Using Dancer-Shared Images
AU - Wen, Jiqing
AU - Li, Xiaopeng
AU - She, James
AU - Park, Soochang
AU - Cheung, Ming
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/5/1
Y1 - 2017/5/1
N2 - Dance performances use body gestures as a language to express emotion, and lighting and background images on the stage to create the scene and atmosphere. In conventional dance performances, the background images are usually selected or designed by professional stage designers according to the theme and the style of the dance. In new media dance performances, the stage effects are usually generated by media editing software. Selecting or producing a dance background is quite troublesome, and is generally carried out by skilled technicians. The goal of the research reported in this paper is to ease this process, meaning dancers can set background images for their dance performances without the need for stage designers. Instead of searching for background images from the sea of available resources, dancers are recommended images they are more likely to use. This paper proposes the idea of a novel system to recommend images based on content-based social computing. A model to predict a dancer's interests in candidate images through social platforms, e.g., Pinterest, is proposed. With the help of such a system, dancers can select from the recommended images and set them as the backgrounds of their dance performances through a media editor. To the best of our knowledge, this would be the first dance background recommendation system for dance performances.
AB - Dance performances use body gestures as a language to express emotion, and lighting and background images on the stage to create the scene and atmosphere. In conventional dance performances, the background images are usually selected or designed by professional stage designers according to the theme and the style of the dance. In new media dance performances, the stage effects are usually generated by media editing software. Selecting or producing a dance background is quite troublesome, and is generally carried out by skilled technicians. The goal of the research reported in this paper is to ease this process, meaning dancers can set background images for their dance performances without the need for stage designers. Instead of searching for background images from the sea of available resources, dancers are recommended images they are more likely to use. This paper proposes the idea of a novel system to recommend images based on content-based social computing. A model to predict a dancer's interests in candidate images through social platforms, e.g., Pinterest, is proposed. With the help of such a system, dancers can select from the recommended images and set them as the backgrounds of their dance performances through a media editor. To the best of our knowledge, this would be the first dance background recommendation system for dance performances.
KW - Dance background
KW - Dance style
KW - Image content
KW - Image recommendation
UR - http://www.scopus.com/inward/record.url?scp=85020188154&partnerID=8YFLogxK
U2 - 10.1109/iThings-GreenCom-CPSCom-SmartData.2016.120
DO - 10.1109/iThings-GreenCom-CPSCom-SmartData.2016.120
M3 - Conference contribution
AN - SCOPUS:85020188154
T3 - Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016
SP - 521
EP - 527
BT - Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016
A2 - Liu, Xingang
A2 - Qiu, Tie
A2 - Li, Yayong
A2 - Guo, Bin
A2 - Ning, Zhaolong
A2 - Lu, Kaixuan
A2 - Dong, Mianxiong
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference on Internet of Things, 12th IEEE International Conference on Green Computing and Communications, 9th IEEE International Conference on Cyber, Physical, and Social Computing and 2016 IEEE International Conference on Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016
Y2 - 16 December 2016 through 19 December 2016
ER -