Abstract: As a crucial problem in computer vision, visual tracking has been studied over decades with a wide sprectrum of applications. In this talk, we will first summarize research conducted in our group on visual tracking with lessens learned and ideas moviated. The, we will introduce in details our recent work of tracking algorithms on single-target tracking, plane object tracking, and multi-target tracking. We will also present our recent work on tracking benchmarks and evaluations.
Bio: Haibin Ling received the B.S. and M.S. degrees from Peking University in 1997 and 2000, respectively, and the Ph.D. degree from the University of Maryland, College Park, in 2006. From 2000 to 2001, he was an assistant researcher at Microsoft Research Asia. From 2006 to 2007, he worked as a postdoctoral scientist at the University of California Los Angeles. In 2007, he joined Siemens Corporate Research as a research scientist. From 2008 to 2019, he worked as a faculty menber of the Department of Computer Sciences at Temple University. In 2019, he joined the Computer Science Department of Stony Brook University (SUNY) as an Empire Innovation Professor. His research interests include computer vision, augmented reality, medical image analysis, and human computer interaction. He received the Best Student Paper Award at the ACM UIST in 2003, and the NSF CAREER Award in 2014. He serves as Associate Editors for several journals including IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), Pattern Recognition (PR), and Computer Vision and Image Understanding (CVIU). He has served or will serve as Area Chairs for CVPR 2014, 2016, 2019 and 2020.