Paper (WACV 2016) “Discovering Picturesque Highlights from Egocentric Vacation Videos”

March 7th, 2016 Irfan Essa Posted in Computational Photography and Video, Computer Vision, Daniel Castro, PAMI/ICCV/CVPR/ECCV, Vinay Bettadapura No Comments »

Paper

  • D. Castro, V. Bettadapura, and I. Essa (2016), “Discovering Picturesque Highlights from Egocentric Vacation Video,” in Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), 2016. [PDF] [WEBSITE] [arXiv] [BIBTEX]
    @InProceedings{    2016-Castro-DPHFEVV,
      arxiv    = {http://arxiv.org/abs/1601.04406},
      author  = {Daniel Castro and Vinay Bettadapura and Irfan
          Essa},
      booktitle  = {Proceedings of IEEE Winter Conference on
          Applications of Computer Vision (WACV)},
      month    = {March},
      pdf    = {http://www.cc.gatech.edu/~irfan/p/2016-Castro-DPHFEVV.pdf},
      title    = {Discovering Picturesque Highlights from Egocentric
          Vacation Video},
      url    = {http://www.cc.gatech.edu/cpl/projects/egocentrichighlights/},
      year    = {2016}
    }

Abstract

2016-Castro-DPHFEVVWe present an approach for identifying picturesque highlights from large amounts of egocentric video data. Given a set of egocentric videos captured over the course of a vacation, our method analyzes the videos and looks for images that have good picturesque and artistic properties. We introduce novel techniques to automatically determine aesthetic features such as composition, symmetry, and color vibrancy in egocentric videos and rank the video frames based on their photographic qualities to generate highlights. Our approach also uses contextual information such as GPS, when available, to assess the relative importance of each geographic location where the vacation videos were shot. Furthermore, we specifically leverage the properties of egocentric videos to improve our highlight detection. We demonstrate results on a new egocentric vacation dataset which includes 26.5 hours of videos taken over a 14-day vacation that spans many famous tourist destinations and also provide results from a user-study to access our results.

 

AddThis Social Bookmark Button

Spring 2016 Teaching

January 10th, 2016 Irfan Essa Posted in Computational Photography, Computational Photography and Video, Computer Vision, Computer Vision No Comments »

My teaching activities for Spring 2016 areBB1162B4-4F87-480C-A850-00C54FAA0E21

AddThis Social Bookmark Button

Presentation at Max-Planck-Institut für Informatik in Saarbrücken (2015): “Video Analysis and Enhancement”

September 14th, 2015 Irfan Essa Posted in Computational Journalism, Computational Photography and Video, Computer Vision, Presentations, Ubiquitous Computing No Comments »

Video Analysis and Enhancement: Spatio-Temporal Methods for Extracting Content from Videos and Enhancing Video OutputSaarbrücken_St_Johanner_Markt_Brunnen

Irfan Essa (prof.irfanessa.com)

Georgia Institute of Technology
School of Interactive Computing

Hosted by Max-Planck-Institut für Informatik in Saarbrucken (Bernt Schiele, Director of Computer Vision and Multimodal Computing)

Abstract 

In this talk, I will start with describing the pervasiveness of image and video content, and how such content is growing with the ubiquity of cameras.  I will use this to motivate the need for better tools for analysis and enhancement of video content. I will start with some of our earlier work on temporal modeling of video, then lead up to some of our current work and describe two main projects. (1) Our approach for a video stabilizer, currently implemented and running on YouTube, and its extensions. (2) A robust and scaleable method for video segmentation. 

I will describe, in some detail, our Video stabilization method, which generates stabilized videos and is in wide use running on YouTube, with Millions of users. Then I will  describe an efficient and scalable technique for spatiotemporal segmentation of long video sequences using a hierarchical graph-based algorithm. I will describe the videosegmentation.com site that we have developed for making this system available for wide use.

Finally, I will follow up with some recent work on image and video analysis in the mobile domains.  I will also make some observations about the ubiquity of imaging and video in general and need for better tools for video analysis. 

AddThis Social Bookmark Button

Presentation at Max-Planck-Institute for Intelligent Systems in Tübingen (2015): “Data-Driven Methods for Video Analysis and Enhancement”

September 10th, 2015 Irfan Essa Posted in Computational Photography and Video, Computer Vision, Machine Learning, Presentations No Comments »

Data-Driven Methods for Video Analysis and EnhancementIMG_3995

Irfan Essa (prof.irfanessa.com)
Georgia Institute of Technology

Thursday, September 10, 2 pm,
Max Planck House Lecture Hall (Spemannstr. 36)
Hosted by Max-Planck-Institute for Intelligent Systems (Michael Black, Director of Percieving Systems)

Abstract

In this talk, I will start with describing the pervasiveness of image and video content, and how such content is growing with the ubiquity of cameras.  I will use this to motivate the need for better tools for analysis and enhancement of video content. I will start with some of our earlier work on temporal modeling of video, then lead up to some of our current work and describe two main projects. (1) Our approach for a video stabilizer, currently implemented and running on YouTube and its extensions. (2) A robust and scalable method for video segmentation.

I will describe, in some detail, our Video stabilization method, which generates stabilized videos and is in wide use. Our method allows for video stabilization beyond the conventional filtering that only suppresses high-frequency jitter. This method also supports the removal of rolling shutter distortions common in modern CMOS cameras that capture the frame one scan-line at a time resulting in non-rigid image distortions such as shear and wobble. Our method does not rely on apriori knowledge and works on video from any camera or on legacy footage. I will showcase examples of this approach and also discuss how this method is launched and running on YouTube, with Millions of users.

Then I will  describe an efficient and scalable technique for spatiotemporal segmentation of long video sequences using a hierarchical graph-based algorithm. This hierarchical approach generates high-quality segmentations and we demonstrate the use of this segmentation as users interact with the video, enabling efficient annotation of objects within the video. I will also show some recent work on how this segmentation and annotation can be used to do dynamic scene understanding.

I will then follow up with some recent work on image and video analysis in the mobile domains.  I will also make some observations about the ubiquity of imaging and video in general and need for better tools for video analysis.

AddThis Social Bookmark Button

Participated in the KAUST Conference on Computational Imaging and Vision 2015

March 1st, 2015 Irfan Essa Posted in Computational Photography and Video, Computer Vision, Daniel Castro, Presentations No Comments »

I was invited to participate and present at the King Abdullah University of Science & Technology Conference on Computational Imaging and Vision (CIV)

March 1-4, 2015
Building 19 Level 3, Lecture Halls
Visual Computing Center (VCC)

Invited Speakers included

  • Shree Nayar – Columbia University
  • Daniel Cremers – Technical University of Munich
  • Rene Vidal –The Johns Hopkins University
  • Wolfgang Heidrich – VCC, KAUST
  • Jingyi Yu –University of Delaware
  • Irfan Essa – The Georgia Institute of Technology
  • Mubarak Shah – University of Central Florida
  • Larry Davis – University of Maryland
  • David Forsyth –University of Illinois
  • Gordon Wetzstein – Stanford University
  • Brian Barsky – University of California
  • Yi Ma – ShanghaiTech University
  • etc.

This event was hosted by the Visual Computing Center (Wolfgang HeidrichBernard GhanemGanesh Sundaramoorthi).

Daniel Castro also attended and presented a poster at the meeting.

2015-03-KUAST

AddThis Social Bookmark Button