报告题目：Graph Decomposition for People Tracking and Pose Estimation
报告时间：12月26日(星期三)上午10:30
报告地点：浙江大学紫金港校区CAD&CG国家重点实验室402会议室
主讲人：汤思宇博士(Max Planck Institute for Intelligent Systems)
主持人：金小刚 教授

Abstract: 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 perceive people's positions, motion and articulated poses in complex visual scenes. 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.

Bio:Siyu Tang is a research group leader at the Max Planck Institute for Intelligent Systems, Germany. 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 a Master degree in media informatics at RWTH Aachen University and a Bachelor degree in computer science at Zhejiang University, China. She was a research intern at the Japanese National Institute of Informatics, under the supervision of Prof. Helmut Prendinger. Dr. Tang received the DAGM-MVTec 2018 Dissertation Award. She was the winner of the multi-object tracking challenge at ECCV’16 and CVPR’17. Her work also received a Best Paper Award at BMVC2018.
https://ps.is.tuebingen.mpg.de/person/stang