Our paper M. Grundmann, V. Kwatra, Daniel Castro, and I. Essa (2012), “Calibration-Free Rolling Shutter Removal,” in IEEE Conference on Computational Photography (ICCP), 2012. (Best Paper Award) [PDF] [WEBSITE] [VIDEO] [DOI] [BIBTEX] @InProceedings{ 2012-Grundmann-CRSR, author = {Matthias Grundmann and Vivek Kwatra and Daniel Castro and Irfan Essa}, awards = {(Best Paper Award)}, booktitle = {{IEEE […]
Presentation at Google I/0 2013 by Matthias Grundmann, John Gregg, and Vivek Kwatra on our Video Stabilizer on YouTube Video stabilization is a key component of YouTubes video enhancement tools and youtube.com/editor. All YouTube uploads are automatically detected for shakiness and suggested stabilization if needed. This talk will describe the technical details behind our fully […]
The Computational Photography MOOC offering in Coursera came to a close with the following final announcement (abridged here) on May 7, 2013. Computational photographers: Thanks for joining us for an engaging 5 weeks of collaboratively learning the wonderful aspects of computational photography. We bid you all farewell now and hope to see some of you […]
We present a novel data-driven technique for radiometric self-calibration of video from an unknown camera. Our approach self-calibrates radiometric variations in video, and is applied as a post-process; there is no need to access the camera, and in particular, it is applicable to internet videos.
Title: Computational Video: Post-processing Methods for Stabilization, Retargeting and Segmentation Matthias GrundmannSchool of Interactive ComputingCollege of ComputingGeorgia Institute of TechnologyDate: February 04, 2013 (Monday)Time: 3:00p – 6:00p ESTLocation: Nano building, 116-118 Abstract: In this thesis, we address a variety of challenges for analysis and enhancement of Computational Video. We present novel post-processing methods to bridge […]
Video Analysis and Enhancement: Video Stabilization and Rolling Shutter Removal on YouTube Irfan Essa Georgia Tech School of Interactive Computing GVU and RIM @ GT Centers October 19, 2012, 3:30 PM, NSH 1305 Abstract In this talk, I will discuss a variety of approaches my group is working on for video analysis and enhancement. In […]
Citation Abstract We propose to learn pixel-level segmentations of objects from weakly labeled (tagged) internet videos. Espe cially, given a large collection of raw YouTube content, along with potentially noisy tags, our goal is to automatically generate spatiotemporal masks for each object, such as dog”, without employing any pre-trained object detectors. We formulate this problem as […]
Video Enhancement and Analysis: From Content Analysis to Video Stabilization for YouTube Irfan Essa Georgia Institute of Technology October 14, 2012 15:00 – 16:00, Huxely Room. South Kensington Campus, Imperial College, London Abstract The talk will describe a variety of efforts undertaken on analysis of video to enhancement and synthesis of video. An overview of […]
Video Stabilization and Rolling Shutter Removal on YouTube Abstract In this talk, I will over a variety of approaches my group is working on for video analysis and enhancement. In particular, I will describe our approach for a video stabilizer (currently implemented on YouTube) and its extensions. This work is in collaboration with Matthias Grundmann […]
At IEEE CVPR 2012 is in Providence RI, from Jun 16 – 21, 2012. Busy week ahead meeting good friends and colleagues. Here are some highlights of what my group is involved with. Paper in Main Conference K. Kim, D. Lee, and I. Essa (2012), “Detecting Regions of Interest in Dynamic Scenes with Camera Motions,” in […]