Prof. Corso moved to the Electrical Engineering and Computer Science department at the University of Michigan in the 8/2014. He continues his work and research group in high-level computer vision at the intersection of perception, semantics/language, and robotics. Unless you are looking for something specific, historically, here, you probably would rather go to his new page.
Video Segmentation Tutorial
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CVPR2014 Tutorial: Video Segmentation


Organizers: Jason Corso (Buffalo), Matthias Grundmann (Google), Irfan Essa (Georgia Tech)
Course Webpage: http://www.cse.buffalo.edu/~jcorso/t/2014S_SEM
Date/Time:June 23 PM (1300--1700)
Location: TBD

Main Tutorial Material

Course Overview: Technology advances have made it quite simple to record a video nearly anytime, anywhere. As a result, we are drowning in video content---YouTube, for example, receives 72 hours of video uploaded every minute. In many applications, there is so much video content that a sufficient supply of human observers to manually tag or annotate the videos is unavailable. Furthermore, these unconstrained videos contain rich and variable content, are acquired from a broad set of devices, and are largely out of the scope of many known techniques; they hence present a rich problem-space for the next steps in computer vision research!

In recent years, segmentation has emerged as a plausible first step in early video processing of unconstrained videos, without needing to make an assumption of a static background as earlier methods have. Video segmentation and over-segmentation, or more commonly supervoxel extraction, is a complementary early video processing step to the more traditional feature extraction, such as STIP and trajectories, and it extends the long history of image segmentation methods. This tutorial will survey and present the important models and algorithms for video segmentation. We will cover direct extensions of image segmentation methods through video-specific spatiotemporal and streaming methods. In addition to core methodological elements, the tutorial will also cover benchmark and evaluation of video segmentation as well as applications of video segmentation. Participants will be introduced to the details of these methods not only through traditional slide presentations but also example implementations through the LIBSVX library.


Course Schedule

This is an estimate of the schedule...
Time Topic Presenter(s) Download
1:00-1:30 Introduction Jason pdf   pptx
1:30-2:00 Graph-based Hierarchical Video Segmentation Matthias key.tbz   pdf
2:00-2:30 Segmentation by Weighted Aggregation Jason pdf   pptx
2:30-3:00 Other Recent Methods Jason
3:00-3:30 Coffee Break
3:30-4:15 Applications of Video Segmentation Irfan and Matthias key.tbz   pdf
4:15-4:45 LIBSVX and Video Segmentation Evaluation Chenliang Xu pdf   pptx
4:45-5:00 Wrap-up All

last updated: Sat Jun 21 07:38:47 2014; copyright jcorso