Abstract：
With the advances of the artificial intelligence, content-based image retrieval can be developed as multi-level schemes with low-level and high-level features involved. In this talk, the functions and extended advantages of the digital halftoning will be introduced. An extremely low complexity compression scheme with the aid of digital halftoning is later presented. As most images are compressed and recorded, compressed domain features are thus intuitively adopted to form the low-level features for the image retrieval. Conversely, features generated by deep learning can better characterize human perception through various operations such as convolution and pooling, and thus achieve effective retrieval performance. At the end of this talk, the fusion descriptors from low- and high-level features will be introduced, and the hybrid image retrieval system will subsequently be demonstrated with practical examples.
Bio：
Prof. Guo received the Ph.D. degree from the Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan, in 2004. He is currently a Professor with the Department of Electrical Engineering and was the Vice Dean of the College of Electrical Engineering and Computer Science, National Taiwan University of Science and Technology, Taipei, Taiwan. His research interests include multimedia signal processing, biometrics, computer vision, and digital halftoning.
Dr. Guo is a senior member of the IEEE and a Fellow of the IET. He received the Outstanding Professor Award on Electrical Engineering from Chinese Institute of Electrical Engineering in 2016, the Best Paper Award from the International Computer Symposium in 2014, the Outstanding youth Electrical Engineer Award from Chinese Institute of Electrical Engineering in 2011, the Outstanding young Investigator Award from the Institute of System Engineering in 2011, the Best Paper Award from the IEEE International Conference on System Science and Engineering in 2011, the Excellence Teaching Award in 2009, the Research Excellence Award in 2008, the Acer Dragon Thesis Award in 2005, the Outstanding Paper Awards from IPPR, Computer Vision and Graphic Image Processing in 2005 and 2006, and the Outstanding Faculty Award in 2002 and 2003.
Dr. Guo is the Chapter Chair of IEEE Signal Processing Society, Taipei Section. He was the General Chair of IEEE International Conference on Consumer Electronics in Taiwan in 2015 and 2016, and was the Technical program Chair for IEEE International Symposium on Intelligent Signal Processing and Communication Systems in 2012, IEEE International Symposium on Consumer Electronics in 2013, and IEEE International Conference on Consumer Electronics in Taiwan in 2014. He has served as a Best Paper Selection Committee member of the IEEE Transactions on Multimedia. Currently, he is Associate Editor of the IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, IEEE Signal Processing Letters, the Information Sciences, the Signal Processing, and Journal of Information Science and Engineering.
