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RGB++: How "Side Information" Improves Computational Photography and Computer Vision

Apr 25, 2013

Information theory and signal processing have classically used the notion of "side information" to formally describe and analyze situations where providing more information to either the encoding or the decoding process improves system performance. We consider and extend this viewpoint to modern day imaging systems, where in addition to images representing visual information, devices also capture a variety of side information. In the ubiquitous smartphone, for example, multiple sensors (microphone, GPS, accelerometer, compass, etc.) augment the two cameras that have become the norm. Additionally, these devices are usually connected to a large network of digital data. This rich "side information" can improve the performance of imaging applications and enable completely new functionality. Using research examples from our group, ranging from near-infrared to semantics, we present applications of such "side information" enabled functionality and improvements for computational photography and computer vision..

Prof. Sabine Süsstrunk, EPFLausanne
Date: 19-3-13
Time: 14:15 -15:45
Location: TU Vienna
Zemanek Lecture Room (Room Number: HHEG01)
HS 13 Ernst Melan
1040 Wien, Karlsplatz 13 (Main building, Stiege VII, 2nd floor)

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Event Location

TU Vienna - Zemanek Lecture Room (Room Number: HHEG01)
1040 Vienna Favoritenstraße 9-11, Stiege III, ground floor, light green area
Vienna
Austria