DEMO (2011): Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths – from Google Research Blog

June 20th, 2011 Irfan Essa Posted in Computational Photography and Video, In The News, Matthias Grundmann, Mobile Computing, PAMI/ICCV/CVPR/ECCV, Vivek Kwatra No Comments »

via Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths – Google Research Blog.

Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths
Posted by Matthias GrundmannVivek Kwatra, and Irfan Essa,

Earlier this year, we announced the launch of new features on the YouTube Video Editor, including stabilization for shaky videos, with the ability to preview them in real-time. The core technology behind this feature is detailed in this paper, which will be presented at the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2011).

Casually shot videos captured by handheld or mobile cameras suffer from significant amount of shake. Existing in-camera stabilization methods dampen high-frequency jitter but do not suppress low-frequency movements and bounces, such as those observed in videos captured by a walking person. On the other hand, most professionally shot videos usually consist of carefully designed camera configurations, using specialized equipment such as tripods or camera dollies, and employ ease-in and ease-out for transitions. Our goal was to devise a completely automatic method for converting casual shaky footage into more pleasant and professional looking videos.

Our technique mimics the cinematographic principles outlined above by automatically determining the best camera path using a robust optimization technique. The original, shaky camera path is divided into a set of segments, each approximated by either a constant, linear or parabolic motion. Our optimization finds the best of all possible partitions using a computationally efficient and stable algorithm.

To achieve real-time performance on the web, we distribute the computation across multiple machines in the cloud. This enables us to provide users with a real-time preview and interactive control of the stabilized result. Above we provide a video demonstration of how to use this feature on the YouTube Editor. We will also demo this live at Google’s exhibition booth in CVPR 2011.

For more details see the Project Site. See the youtube video of the system on youtube. See the paper in PDF, and a technical video of the work.

Full paper is

 

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PhD Fellowships from Google Research for Matthias Grundmann

May 16th, 2011 Irfan Essa Posted in Awards, In The News, Matthias Grundmann No Comments »

Congratulations to Matthias Grundmann, winner of the Google PhD Fellowship in Computer Vision for 2012.

via PhD Fellowships – Google Research.

Google PhD Fellowship Program Overview

Nurturing and maintaining strong relations with the academic community is a top priority at Google. The Google U.S./Canada PhD Student Fellowship Program was created to recognize outstanding graduate students doing exceptional work in computer science, related disciplines, or promising research areas. Last year we awarded 14 unique fellowships to some amazing students in the US and Canada:

  • Matthias Grundmann, Google U.S./Canada Fellowship in Computer Vision (Georgia Institute of Technology)
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Going Live on YouTube (2011): Lights, Camera… EDIT! New Features for the YouTube Video Editor

March 21st, 2011 Irfan Essa Posted in Computational Photography and Video, Google, In The News, Matthias Grundmann, Multimedia, Vivek Kwatra, WWW No Comments »

via YouTube Blog: Lights, Camera… EDIT! New Features for the YouTube Video Editor.

  • M. Grundmann, V. Kwatra, and I. Essa (2011), “Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. [PDF] [WEBSITE] [VIDEO] [DEMO] [DOI] [BLOG] [BIBTEX]
    @InProceedings{    2011-Grundmann-AVSWROCP,
      author  = {M. Grundmann and V. Kwatra and I. Essa},
      blog    = {http://prof.irfanessa.com/2011/06/19/videostabilization/},
      booktitle  = {Proceedings of IEEE Conference on Computer Vision
          and Pattern Recognition (CVPR)},
      demo    = {http://www.youtube.com/watch?v=0MiY-PNy-GU},
      doi    = {10.1109/CVPR.2011.5995525},
      month    = {June},
      pdf    = {http://www.cc.gatech.edu/~irfan/p/2011-Grundmann-AVSWROCP.pdf},
      publisher  = {IEEE Computer Society},
      title    = {Auto-Directed Video Stabilization with Robust L1
          Optimal Camera Paths},
      url    = {http://www.cc.gatech.edu/cpl/projects/videostabilization/},
      video    = {http://www.youtube.com/watch?v=i5keG1Y810U},
      year    = {2011}
    }

Lights, Camera… EDIT! New Features for the YouTube Video Editor

Nine months ago we launched our cloud-based video editor. It was a simple product built to provide our users with simple editing tools. Although it didn’t have all the features available on paid desktop editing software, the idea was that the vast majority of people’s video editing needs are pretty basic and straight-forward and we could provide these features with a free editor available on the Web. Since launch, hundreds of thousands of videos have been published using the YouTube Video Editor and we’ve regularly pushed out new feature enhancements to the product, including:

  • Video transitions (crossfade, wipe, slide)
  • The ability to save projects across sessions
  • Increased clips allowed in the editor from 6 to 17
  • Video rotation (from portrait to landscape and vice versa – great for videos shot on mobile)
  • Shape transitions (heart, star, diamond, and Jack-O-Lantern for Halloween)
  • Audio mixing (AudioSwap track mixed with original audio)
  • Effects (brightness/contrast, black & white)

A new user interface and project menu for multiple saved projects

While many of these are familiar features also available on desktop software, today, we’re excited to unveil two new features that the team has been working on over the last couple of months that take unique advantage of the cloud:

Stabilizer

Ever shoot a shaky video that’s so jittery, it’s actually hard to watch? Professional cinematographers use stabilization equipment such as tripods or camera dollies to keep their shots smooth and steady. Our team mimicked these cinematographic principles by automatically determining the best camera path for you through a unified optimization technique. In plain English, you can smooth some of those unsteady videos with the click of a button. We also wanted you to be able to preview these results in real-time, before publishing the finished product to the Web. We can do this by harnessing the power of the cloud by splitting the computation required for stabilizing the video into chunks and distributed them across different servers. This allows us to use the power of many machines in parallel, computing and streaming the stabilized results quickly into the preview. You can check out the paper we’re publishing entitled “Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths.” Want to see stabilizer in action? You can test it out for yourself, or check out these two videos. The first is without stabilizer.

And now, with the stabilizer:

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In the News (2009): CNN.com “Augmenting Earth Maps”

October 13th, 2009 Irfan Essa Posted in In The News, Kihwan Kim 1 Comment »

Video – Breaking News Videos from CNN.com.

Check out the media coverage of our new paper to appear in ISMAR 2009, in October.

Also see

  • “Latest videos makes Google Earth cities bustle” New Scientist (Sep 30, 2009 Issue)
  • “Video: Google Earth animated with real time human and vehicular traffic” Endgadget (Sep 30, 2009)
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Time Magazine (2009) Article “Can Computer Nerds Save Journalism?”

June 8th, 2009 Irfan Essa Posted in Computational Journalism, In The News, Interesting No Comments »

Can Computer Nerds Save Journalism?, TIME Magazine, by MATT VILLANO, June 8, 2009

EXCERPT

“At the Georgia Institute of Technology in Atlanta, a three-year-old program in “computational journalism” helps computer-science majors study how journalists gather, organize and utilize information, then take these workflows and see how technology can make the processes easier.”

Full article here. Also see CnJ site.

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INTERESTING: “Deep Throat Meets Data Mining”

December 24th, 2008 Irfan Essa Posted in Computational Journalism, In The News, Interesting No Comments »

“Deep Throat Meets Data Mining”

by JOHN MECKLIN

Dec 23, 2008 in Miller-McCune

If you pay passing attention to the media landscape, you know that most mainstream news outlets have had their business models undermined by the digital revolution. As their general-interest monopolies have been pillaged by niche online competitors, traditional news organizations have lost revenue and cachet, laying off journalists in waves that have grown into tsunamis. This process has created dire prospects for the future of investigative reporting, often seen as the most costly of journalistic forms.”

Goes on to mention Computational Journalism and our (at GA Tech) and recent Duke University’s efforts in this space and few others.

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Awarded the “GVU 15 years of Impact Award”

October 25th, 2007 Irfan Essa Posted in Events, In The News, Research No Comments »

Jim Foley and Irfan EssaThe Award

Awarded the “GVU 15 years of Impact Award” at GVU 15 Anniversary Celebration and Symposium on October 25, 2007.

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GT Research Horizons — Fall 2003

October 30th, 2003 Irfan Essa Posted in Aware Home, Health Systems, Human Factors, In The News, Intelligent Environments, Research No Comments »

GT Research Horizons — Fall 2003

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NY Times Article (2001): “Smart Home, to Avoid the Nursing Home”

April 5th, 2001 Irfan Essa Posted in Aware Home, In The News, Intelligent Environments, Research No Comments »

Anne Eisenberg (2001)“A ‘Smart’ Home, to Avoid the Nursing Home” New York Times Circuits Section,

April 5, 2001 Issue

Quote from the Article: “Cameras are going to rule one day at the Georgia Tech house, though, staff members there say. Dr. Irfan A. Essa, a computer science professor at Georgia Tech, is one of the people building a tracking system, based on video cameras, that will one day replace radio frequency tags. ”We can locate where the person is,” Dr. Essa said, ”and make a first-level guess at where this person is heading using the optical sensors.””

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NYT Science Times (1997): “Laugh and Your Computer Will Laugh With You, Someday”

January 7th, 1997 Irfan Essa Posted in Face and Gesture, In The News, Research No Comments »

Daniel Goldman (1997 “Laugh and Your Computer Will Laugh With You, Someday” Jan 7, 1997 Issue, New York Times, Science Times

Quote from the article: “Emotions like fear, sadness and anger each announce themselves through a unique signature of changes in facial muscle, vocal inflection, physiological arousal, and other such cues. Building on techniques of pattern recognition already used for computer comprehension of words and images, Dr. Irfan Essa, a computer scientist at Georgia Tech, has constructed a computer system that can read people’s emotions from changes in their facial expression.”

This image was used in the article.

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