Interaction art using Video Synthesis Technology
- Authors
- 김성수; 엄현영; 임찬
- Issue Date
- Jun-2019
- Publisher
- 국제문화기술진흥원
- Keywords
- Interactive Art; Deep Learning; GAN; VVVV
- Citation
- The International Journal of Advanced Culture Technology, v.7, no.2, pp.195 - 200
- Journal Title
- The International Journal of Advanced Culture Technology
- Volume
- 7
- Number
- 2
- Start Page
- 195
- End Page
- 200
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/34940
- ISSN
- 2288-7202
- Abstract
- Media art, which is a combination of media technology and art, is making a lot of progress in combination with AI, IoT and VR. This paper aims to meet people's needs by creating a video that simulates the dance moves of an object that users admire by using media art that features interactive interactions between users and works. The project proposed a universal image synthesis system that minimizes equipment constraints by utilizing a deep running-based Skeleton estimation system and one of the deep-running neural network structures, rather than a Kinect-based Skeleton image. The results of the experiment showed that the images implemented through the deep learning system were successful in generating the same results as the user did when they actually danced through inference and synthesis of motion that they did not actually behave.
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