UMBC High Performance Computing Facility
Please note that this page is under construction. We are documenting the
240-node cluster maya that will be available after Summer 2014.
Currently, the 84-node cluster tara still operates independently,
until it becomes part of maya at the end of Summer 2014.
Please see the 2013 Resources Pages under the Resources tab for tara information.
Using Computer Vision to Create 3D Forest Models from
Thousands of Aerial Photos
Dr. Erle Ellis - Associate Professor, UMBC GES
Dr. Marc Olano - Associate Professor, UMBC CSEE
Dr. Matthias Gobbert - Associate Professor, UMBC Math & Stat
Jonathan Dandois - Graduate Student, UMBC GES
Yu Wang - Graduate Student, UMBC CSEE
Christopher Leeney - BS/MS Student, UMBC GES
Dr. Noah Snavely - Assistant Professor, Cornell CS
Computer vision structure from motion (SfM) algorithms make it
possible to generate accurate 3D reconstructions of forest canopy
structure and composition using thousands of overlapping aerial photos.
This process has large computation demands and current reconstructions
based on thousands of images require weeks of processing in serial,
making it impractical for experimentation or widespread application.
Working with HPCF will improve our ability to use SfM for reconstructing
forest canopies to study forest carbon and diversity and will also make
it possible to develop an understanding of the functioning of these
algorithms in forested landscapes.
For more information please visit our website: