Event Location: NSH 1109
Bio: Kshitiz Garg is a research scientist and software developer at
intuVision. His research interests are in the areas of computer vision,
pattern recognition and computer graphics. He has a Masters in Physics
and a PhD. in Computer Science from Columbia University, NY. He
specializes in physics-based modeling and algorithm development. During
his graduate work he developed physics based models for the intensity
fluctuations produced by rain in images. He is also interested in
Computer Graphics and has developed efficient algorithms for realistic
rendering of rain. Since joining the intuVision team, he has worked on
algorithms to improve object tracking and recognition especially in the
presence of background motion, illumination changes and shadows. He is
the research lead for development of intuVision’s object
classification, face detection, and soft biometry algorithms.

Abstract: Rain produces sharp intensity fluctuations in images and videos which
severely degrade the performance of outdoor vision systems. Considering
that bad weather is common, a city like New York has bad weather 23% of
time, it is important to remove the visual effects of rain to make
outdoor vision robust. In contrast, in graphics, rain effects are
desirable. They are often used in movies to convey scene emotions and in
other graphics applications, such as games, to enhance realism. In this
talk, I will present rain from the perspective of vision and graphics.
I will show how physics based modeling of the visual appearance of rain
leads to efficient algorithms both for handling its effects in vision
and for its realistic rendering in graphics. I will also briefly discuss
some of the recent projects I have done on recognition and tracking at
intuVision.