GUO JIE
@sust.edu.cn
College of Design and Art
Shaanxi University of Science and Technology
Guo Jie is an associate professor at the College of Design and Art at Shaanxi University of Science and Technology. He holds a bachelor's degree and a master's degree from the Xi'an Academy of Fine Arts and a PhD from the Faculty of Decorative Arts at Silpakorn University. His main research direction is digital media art and cultural heritage protection.
EDUCATION
Master's degree from Xi'an Academy of Fine Arts
PhD at the Faculty of Decorative Arts, Silpakorn University
RESEARCH, TEACHING, or OTHER INTERESTS
Arts and Humanities, Visual Arts and Performing Arts
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Atithep Chaetnalao and Jie Guo
Inderscience Publishers
Jianjun Zhang and Jie Guo
Hindawi Limited
In recent years, the interdisciplinary exploration of combining traditional visual communication design with somatosensory interaction technology has become a new form of artistic expression. In order to explore the feasibility of somatosensory interaction technology in visual communication design, this study proposes a 2D dynamic graphic generation method based on somatosensory interaction parameterisation and uses traditional Chinese elements as an example for specific applications in visual communication design. Firstly, the motion parameters recognised using the Kinect somatosensory interaction device are bound to the function variables used to generate the images in the development environment, thus enabling human somatosensory interaction with different characters in the scene. Secondly, a linear discriminant analysis based on kernel functions is used to reduce the dimensionality of the vector space, thus solving the problem of real-time and accurate capture of human movements. Then, using the skeletal parameter binding technique, the association between the motion parameters of the somatosensory interaction and the two-dimensional dynamic graphics is achieved. The experimental results show that the visual communication technique based on somatosensory interaction has a high recognition accuracy. Distinguished from traditional digital video, the proposed method can greatly enrich the visual representation of traditional Chinese elements.