"At-a-glance" Visualization of Highlights in Raw Personal Videos
Speaker: Prof. Min Sun (孫民 教授 )
(Department of Electrical Engineering, National Tsing Hua University)
Topic: "At-a-glance" Visualization of Highlights in Raw Personal Videos
Date: Wednesday, 10 Dec. 2014, 1:20pm ~ 3:00pm
Place: R105 Delta Building (台達館)
Abstract:
Nowadays, people share tons of images and videos online. However, raw personal videos typically will rarely be watched again, since they are long and boring most of the time. Our research focuses on generating an "at-a-glance" visualization of highlights in raw person videos. We have two related work for this project. Our first work, "Ranking Domain-specific Highlights by Analyzing Edited Videos" focuses on automatically finding highlights in raw personal videos. Our second work,"Salient Montages from Unconstrained Videos" focuses on automatically generating an at-a-glance visualization (referred to as salient montages) of highlights in raw personal videos.
Bio:
Min Sun is an assistant professor in EE department at NTHU. Before joining NTHU he was a postdoctoral researcher in the Computer Science and Engineering department at the University of Washington (UW) working with Steve Seitz and Ali Farhadi. He graduated from the University of Michigan at Ann Arbor with a Ph.D. degree and Stanford University with a M.Sc. degree. His research interests include object recognition, human pose estimation, and scene understanding in both 2D and 3D. Most recently, he focuses on developing scalable methods for object categorization and video analysis in the age of big data. He has won the best paper award in 3DRR and was also a recipient of W. Michael Blumenthal Family Fund Fellowship.
(Department of Electrical Engineering, National Tsing Hua University)
Topic: "At-a-glance" Visualization of Highlights in Raw Personal Videos
Date: Wednesday, 10 Dec. 2014, 1:20pm ~ 3:00pm
Place: R105 Delta Building (台達館)
Abstract:
Nowadays, people share tons of images and videos online. However, raw personal videos typically will rarely be watched again, since they are long and boring most of the time. Our research focuses on generating an "at-a-glance" visualization of highlights in raw person videos. We have two related work for this project. Our first work, "Ranking Domain-specific Highlights by Analyzing Edited Videos" focuses on automatically finding highlights in raw personal videos. Our second work,"Salient Montages from Unconstrained Videos" focuses on automatically generating an at-a-glance visualization (referred to as salient montages) of highlights in raw personal videos.
Bio:
Min Sun is an assistant professor in EE department at NTHU. Before joining NTHU he was a postdoctoral researcher in the Computer Science and Engineering department at the University of Washington (UW) working with Steve Seitz and Ali Farhadi. He graduated from the University of Michigan at Ann Arbor with a Ph.D. degree and Stanford University with a M.Sc. degree. His research interests include object recognition, human pose estimation, and scene understanding in both 2D and 3D. Most recently, he focuses on developing scalable methods for object categorization and video analysis in the age of big data. He has won the best paper award in 3DRR and was also a recipient of W. Michael Blumenthal Family Fund Fellowship.