AIC Seminar Series
Video processing using additional information
|Mahesh Ramachandran||University of Maryland||[Home Page]|
Notice: Hosted by Aravind Sundaresan. Note the non-usual day (Friday) and time (11am).
Date: 2009-09-04 at 11:00
Location: EJ228 (SRI E building) (Directions)
Present day computer vision problems involve processing and deriving
information from long video sequences. Because of the tough challenges
in vision, an important research focus has been to develop algorithms
for video processing using additional measurements available along with
image datasets. Video processing using additional information has gained
interest because of the widespread availability of sensors like inertial
measurement units, rangefinders etc. along with video cameras in several
In this talk, we primarily focus on an algorithm for fast structure from
motion from image sequences using additional measurements about the
vertical direction (gravity) and height of the camera. Using the assumed
additional information, we derive a fast, scalable and parallelizable
algorithm for structure from motion. We argue that this form of
additional information is available in several different problem
scenarios. We illustrate competitive results on several challenging
datasets including the VIVID aerial dataset and the Google StreetView
We will also briefly describe work on video stabilization, mosaicing and
moving object detection in aerial sequences with and without additional
Bio for Mahesh Ramachandran||
Mahesh Ramachandran is a Ph.D. candidate in the Dept of Electrical
Engineering working with Prof. Rama Chellappa. He previously obtained
his Masters degree from the same department, and his Bachelors degree
(Electrical Engineering) from the Indian Institute of Technology Madras.
In the summer of 2008, he worked in the StreetView group in Google Inc,
Mountain View, CA. In the summer of 2007, he worked in the Visualization
and Computer Vision Laboratory in GE Research, Schenectady, NY.
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