Emotion Recognition from Facial Expression Videos and its Applications
|讲座名称：||Emotion Recognition from Facial Expression Videos and its Applications|
讲座题目：Emotion Recognition from Facial Expression Videos and its Applications
讲座时间：2017年1月03日（星期二） 上午 9:00-10:00
讲座摘要: Facial expression analysis has becoming a popular research topic in recent years due to multidiscipline collective efforts from researchers in computer science, psychology, and cognitive science. Artificial intelligence has made significant contribution for facial expression analysis that can be used for the design of advanced human machine interaction system, intelligent robots and computer games. It can also be used for human mental health analysis such as dementia, autism and clinical diagnosis application such as shoulder pain and low back pain. This talk will address the problem on how to capture emotion information from facial expressions by generate statistic and dynamic features and how to use advanced machine learning methods to modelling the dynamic of the facial expression sequences to achieve the higher recognition rate. The talk will cover the 2 international challenging winning works as well as some recent work based deep learning. In the end, the applications of the facial expression recognition will be viewed.
报告人简介：Dr Hongying Meng is a senior lecturer (associate professor) in the Department of Electronic and Computer Engineering at Brunel University London, UK. He is also a member of Institute of Environment, Health and Societies, and Human Centred Design Institute (HCDI) there. He obtained BSc, MSc and PhD degrees all from Xi’an Jiaotong University. He worked at Tsinghua University and other universities in UK before joining Brunel. He has a wide research interests including digital signal processing, machine learning, human computer interaction, image processing and embedded systems. His present research focuses on image processing and machine learning with applications, such as facial expression analysis. He has developed two different facial expression analysis systems that won the international challenge completions AVEC2011 (http://sspnet.eu/avec2011/) and AVEC2013 (http://sspnet.eu/avec2013/) respectively. This year, he was invited for a talk on Deep Learning for Facial Expression Analysis at Deep Learning Summit in London on Sept. 22 - 23. He has authored or co-authored about 90 papers with more than 1300 citations.
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