报告题目：Hot or Cute? machine learning of sociopsychological first impressions of faces
演讲人：Xiaolin Wu (武筱林)，IEEE Fellow
单位：Department of Electrical & Computer Engineering,McMaster University
Abstract：The main objective of our research is to explore the potential of supervised machine learning in face-induced social cognition, riding on the momentum of much heralded successes of face processing, analysis and recognition on the tasks of biometric-based identification. We present a case study of automated statistical inference on sociopsychological perceptions of female faces controlled for race, attractiveness, age and nationality. Our empirical evidences point to the possibility of training machine learning algorithms, using annotated face images in the Internet, to predict the first impression of a non-acquaintance in terms of personality traits and demeanors. In addition, we also developed new techniques for enlarging the sample set of annotated face images by an order of magnitude and for protecting the privacy of subjects in scientific studies.
Brief biography: Xiaolin Wu, Ph.D. in computer science, University of Calgary, Canada, 1988. Dr. Wu started his academic career in 1988, and has since been on the faculty of Western University, Canada, New York Polytechnic University (NYU Poly), and currently McMaster University, where he is a professor at the Department of Electrical & Computer Engineering and holds the NSERC senior industrial research chair in Digital Cinema. His research interests include image processing, network-aware visual computing and communication, multimedia signal coding, and multiple description coding. He has published over three hundred research papers and holds five patents in these fields. Dr. Wu is an IEEE fellow, a McMaster distinguished engineering professor, a past associated editor of IEEE Transactions on Image Processing and IEEE Transactions on Multimedia, and served on the technical committees of many IEEE international conferences/workshops. Dr. Wu received numerous international awards and honors.