报告题目：Mining Middle Level Representations for Human Action Recognition
报告人：Yu Qiao （乔宇）
报告人简历：Yu Qiao received Ph.D from the University of Electro-Communications, Japan, in 2006. He was a JSPS fellow and then a project assistant professor with the University of Tokyo from 2007 to 2010. Now he is a professor with the Shenzhen Institutes of Advanced Technology, the Chinese Academy of Science. His research interests include pattern recognition, computer vision, multimedia, image processing and machine learning. He has published more than 90 papers in these fields. He received the Lu Jiaxi young researcher award from the Chinese Academy of Science.
报告摘要：Human action recognition is receiving extensive research interests in computer vision nowadays due to its wide applications in surveillance, human-computer interface, sports video analysis, and content based video retrieval. The challenges of action recognition come from background clutter, viewpoint changes, and motion and appearance variations. In this talk, we will show our two recent works (CVPR13, ICCV13) to address these challenges. Both of them develop middle level parts for action representation, but different in how to define and mine the parts. Experimental results on large public datasets demonstrate the effectiveness of our approach.