Publications

@inproceedings{2016-Castro-DPHFEVV,

title = {Discovering Picturesque Highlights from Egocentric Vacation Video},

author = {Daniel Castro and Vinay Bettadapura and Irfan Essa},

url = {https://ieeexplore.ieee.org/document/7477707

http://www.cc.gatech.edu/cpl/projects/egocentrichighlights/

https://youtu.be/lIONi21y-mk},

doi = {10.1109/WACV.2016.7477707},

year  = {2016},

date = {2016-03-01},

urldate = {2016-03-01},

booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},

abstract = {We 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.

},

keywords = {computational photography, computational video, computer vision, WACV},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2014-Ahsan-TSVFSM,

title = {Towards Story Visualization from Social Multimedia},

author = {Unaiza Ahsan and Irfan Essa},

url = {http://compute-cuj.org/cj-2014/cj2014_session5_paper2.pdf

http://symposium2014.computation-and-journalism.com/},

year  = {2014},

date = {2014-10-01},

urldate = {2014-10-01},

booktitle = {Proceedings of Symposium on Computation and Journalism},

keywords = {computational journalism, computational photography},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2012-Grundmann-CRSR,

title = {Calibration-Free Rolling Shutter Removal},

author = {Matthias Grundmann and Vivek Kwatra and Daniel Castro and Irfan Essa},

url = {http://www.cc.gatech.edu/cpl/projects/rollingshutter/

https://research.google.com/pubs/archive/37744.pdf

https://youtu.be/_Pr_fpbAok8},

doi = {10.1109/ICCPhot.2012.6215213},

year  = {2012},

date = {2012-01-01},

urldate = {2012-01-01},

booktitle = {IEEE Conference on Computational Photography (ICCP)},

publisher = {IEEE Computer Society},

abstract = {We present a novel algorithm for efficient removal of rolling shutter distortions in uncalibrated streaming videos. Our proposed method is calibration free as it does not need any knowledge of the camera used, nor does it require calibration using specially recorded calibration sequences. Our algorithm can perform rolling shutter removal under varying focal lengths, as in videos from CMOS cameras equipped with an optical zoom. We evaluate our approach across a broad range of cameras and video sequences demonstrating robustness, scaleability, and repeatability. We also conducted a user study, which demonstrates preference for the output of our algorithm over other state-of-the art methods. Our algorithm is computationally efficient, easy to parallelize, and robust to challenging artifacts introduced by various cameras with differing technologies.

},

keywords = {awards, best paper award, computational photography, computational video, computer graphics, computer vision, ICCP},

pubstate = {published},

tppubtype = {inproceedings}

}