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Computational Inference of Emotion in Images
Date: 2016/5/30             Browse: 355

Computational Inference of Emotion in Images

Speaker: Jiebo Luo

Time: May 30, 10:00am - 11:00am.

Location: Room 306, Teaching Building

Abstract:

With the recent successes in using deep learning techniques to solve computer vision problems, the performances of the state of the art algorithms in many areas, especially object recognition, have been dramatically improved. Researchers are now inspired to address yet more challenging problems, such as associating pictures with aesthetics, and have also reported progress. One remaining final frontier in extracting meaning from images is related to the recognition of emotions that images arouse in humans. The key challenges are the loose and highly abstract nature of semantics associated with emotions. We will discuss how to effectively employ a data-intensive approach to emotion recognition in images, as well as multimedia that include both image and text information.

Bio:

Professor Jiebo Luo joined the University of Rochester (UR) in 2011 after a prolific career of over fifteen years at Kodak Research Laboratories. He has been involved in numerous technical conferences, including serving as the program co-chair of ACM Multimedia 2010, IEEE CVPR 2012, and IEEE ICIP 2017. He has served as the Editor-in-Chief of the Journal of Multimedia, and on the editorial boards of the IEEE  Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Multimedia (TMM), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT),  Pattern Recognition, Machine Vision and Applications, and Journal of Electronic Imaging. He is a  Fellow of the SPIE, IEEE, and IAPR. He is a Data Science Distinguished Researcher with the CoE  Goergen Institute for Data Science (IDS) at UR.

SIST-Seminar 16012