Laura Sevilla-Lara
lsevilla at cs.umass.edu



Hello there

I am now a postdoc at the Max Planck Institute for Intelligent Systems, where I work with Prof. Michael J. Black. I'm mostly interested in how to integrate high level information (such as recognition) into low level vvision (such as motion estimation).

I received my PhD from UMass in February 2015, where I worked at the Computer Vision Lab under the supervision of Prof. Erik Learned-Miller. During my PhD, my focus was on long-range motion estimation (object tracking and optical flow). For this, I collaborated with Prof. Michael J. Black. I also worked on applications of motion estimation on real world videos with Eli Shechtman.

Before coming to UMass I received my undergrad degree in Computer Science in University of Granada and my masters from Brown University. This was possible thanks to the funding I received as a fellow of Fundacion Caja Madrid. I also had the opportunity of interning at Apple for a summer.

Here is my Resume.


Publications:

Laura Sevilla-Lara, Jonas Wulff, Kalyan Sunkavalli and Eli Shechtman.
Smooth Loops from Unconstrained Video
Proceedings of the Eurographics Symposium on Rendering (EGSR), 2015
[pdf] [project page]

Laura Sevilla-Lara
Long Range Motion Estimation and Applications
PhD Thesis, Department of Computer Science, University of Massachusetts Amherst, February 2015
[pdf]

Laura Sevilla-Lara, Deqing Sun, Erik Learned-Miller and Michael J. Black.
Optical Flow Estimation with Channel Constancy
Proceedings of the European Conference in Computer Vision (ECCV), 2014.
[pdf] [project page]

Benjamin Mears, Laura Sevilla-Lara and Erik Learned-Miller.
Distribution Fields with Adaptive Kernels for Large Displacement Image Alignment
Proceedings of the British Machine Vision Conference (BMVC), 2013.
[pdf] [Code]

Laura Sevilla-Lara and Erik Learned-Miller.
Distribution Fields for Tracking
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.
[pdf] [project webpage] [MATLAB code]

Laura Sevilla-Lara and Erik Learned-Miller
Distribution Fields
Technical Report UM-CS-2011-027, Dept. of Computer Science, University of Massachusetts Amherst, 2011.
[pdf]


Personal:

Here is an iPhone App we made for bill recognition for people who are visually impaired.

I love taking pictures



140 Governors Dr. 01002 Amherst, MA
Computer Vision Lab
Department of Computer Science
University of Massachusetts - Amherst