报告题目：Combinatorial Image and Video Analysis
报告人：Dr. Siyu Tang, Research Group Leader, Max Planck Institute for Intelligent Systems
报告摘要：Understanding people in images and videos is a problem studied intensively in computer vision. While continuous progress has been made, occlusions, cluttered background, complex poses and large variety of appearance remain challenging, especially for crowded scenes. In this talk, I will explore the algorithms and tools that enable computer to interpret people's position, motion and articulated poses in complex visual scenes. More specifically, I will discuss an optimization problem whose feasible solutions relate one-to-one to the decompositions of a graph. I will highlight the applications of this problem in computer vision, which range from multi-person tracking to motion segmentation. I will also cover an extended optimization problem whose feasible solutions define a decomposition of a given graph and a labeling of its nodes with the application on multi-person pose estimation.
讲者简介：Dr. Siyu Tang is a research group leader in the Department of Perceiving Systems at the Max Planck Institute for Intelligent Systems, Germany.
She was a postdoctoral researcher at the Max Planck Institute for Intelligent Systems, advised by Michael Black. She finished her PhD (summa cum laude) at the Max Planck Institute for Informatics, under the supervision of Prof. Bernt Schiele. Before that, she received Master degree in Computer Science at RWTH Aachen University, advised by Prof. Bastian Leibe and Bachelor degree in the Computer Science and Technology Department at Zhejiang University, China. She was a research intern at the National Institute of Informatics, under the supervision of Prof. Helmut Prendinger.