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基本资料

姓名:金功勋

学历/学位:博士

职称/职务:助理教授

教师介绍

Kanoksak Wattanachote received the Ph.D. degree from the Department of Computer Science and Information Engineering, National Central University, Taiwan, the M.S. degree in information management from the School of Advanced Technologies, Asian Institute of Technology, Thailand, and the B.S. degree in statistics from the Faculty of Science, Srinakharinwirot University, Thailand. He is currently working for School of Information Science and Technology, as a faculty member at Guangdong University of Foreign Studies.

His research interests are in the areas of computer vision, image processing, image forensics, JPEG analysis, video editing, and interactive multimedia but. In computer vision researches now, he emphasizes motion recognition on dynamic textures. Several kinds of motion data are extracted to study about: motion pattern, motion periodicity, covariance stationarity etc. Machine learning tools such as support vector machine (SVM) will be concern. For periodicity analysis, singular value decomposition (SVD) is concern for vector analysis. His fields of interest are also including Big Data technologies and Web security.

Selected Publications (sorted by year)

1. Kanoksak Wattanachote, Yongyi Gong, Wenyin Liu, and Yong Wang, “Video detection for dynamic fire texture by using motion pattern recognition,” in Intelligent Systems Conference (IntelliSys) 2018, London, United Kingdom, September 2018.

2. Kanoksak Wattanachote, Zehang Lin, Mingchao Jiang, Liuwu Li, Gongliang Wang, and Wenyin Liu, “An investigation on motion periodic series for fire and smoke textures characteristic identification,” in the 10th IEEE International Conference on Ubi-media Computing and Workshops, Pattaya, Thailand, pp 1-6, 2017.

3. Kanoksak Wattanachote, Yong Wang, Timothy K. Shih, Hui-Huang Hsu, and Wenyin Liu, “Dynamic textures and covariance stationary series analysis using strategic motion coherence,” in the 31st IEEE International Conference on Advanced Information Networking and Applications (AINA), pp 205-212, 2017.

4. Kanoksak Wattanachote, Kuan Li, Yong Wang, Timothy K. Shih, and Wenyin Liu, “Preliminary investigation on stationarity of dynamic smoke texture and dynamic fire texture based on motion coherent metric,” in the IEEE International Conference on Machine Vision and Information Technology, pp 99-104, 2017.

5. Kanoksak Wattanachote, Zehang Lin, Mingchao Jiang, Liuwu Li, Gongliang Wang, and Wenyin Liu, “Fire and smoke dynamic textures characterization by applying periodicity index based on motion features,” in the 11th International Conference on Computer Vision Systems, Shenzhen, China, pp 507-517, 2017.

6. Kanoksak Wattanachote and Timothy K. Shih, “Automatic dynamic texture transformation based on a new motion coherence metric,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 26(10), pp 1805-1820, 2016. SCI (IF: 3.599) http://video.minelab.tw/DTT/

7. Kanoksak Wattanachote, Timothy K. Shih, Senior Member, IEEE, Wen-Lung Chang and Hon-Hang Chang, “Tamper detection of JPEG image due to seam modifications,” IEEE Transactions on Information Forensics & Security (TIFS), 10(12), pp 2477-2491, 2015. SCI (IF: 4.332) http://video.minelab.tw/DETS/

8. W. G. C. W. Kumara, Kanoksak Wattanachote, Batbaatar Battulga, Timothy K. Shih, and Wu-Yuin Hwang, “A Kinect-based assessment system for smart classroom,” in the International Journal of Distance Education Technologies (IJDET), 13(2), pp 34-53, 2015. EI

9. Kanoksak Wattanachote, Kumara W. G. C. W., Timothy K. Shih and Klimenko Andrei, “Automatic creation of dynamic patches in special effect videos,” in the 25th Anniversary International Conference GraphiCon, Institute of Computing for Physics and Technology, Park Drakino, Protvino, Russia, September 22-25, 2015.

10. Guangyu Piao, Xiaokang Zhou, Qun Jin, Shoji Nishimura, Kanoksak Wattanachote, Timothy K. Shih and Neil Y.Yen, “Eye-tracking experiment design for extraction of viewing patterns in social media,” in the 10th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC), pp 308-313, 2013.

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