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The Taub Faculty of Computer Science Events and Talks

Pixel Club: Light Invariant Video Imaging –Capabilities and Applications
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Amir Kolaman (Ben-Gurion University)
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Tuesday, 01.11.2016, 11:30
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EE Meyer Building 1061
Controlled light conditions improve considerably the performance of most computer vision algorithms. Dynamic light conditions create varying spatial changes in color and intensity across the scene. These condition, caused by a moving shadow for example, force developers to create algorithms which are robust to such variations. We suggest a computational camera which produces images that are not influenced by environmental variations in light conditions. The key insight is that many years ago, similar difficulties were already solved in radio communication; As a result each channel is immune to interference from other radio channels. Amplitude Modulated (AM) video camera separates the influence of a modulated light from other unknown light sources in the scene; Causing the AM video camera frame to appear the same - invariant of light conditions creating a Light Invariant Video Imaging system. We built a prototype of this system by using off the shelf hardware and tested it. This camera was used to demonstrate color constancy, shadow removal and contrast enhancement in real time. We show theoretically and empirically that: 1. the proposed system can produce images with similar noise levels as a standard camera. 2. The images created by such camera are almost completely immune to temporal, spatial and spectral changes in the background light.

Short bio:
Amir Kolaman received his B.Sc. in electrical engineering and M.Sc. in electro-optical engineering the degree from Ben-Gurion University of the Negev, Beersheba, Israel, in 2005 and 2011, respectively. He is currently pursuing a Ph.D. degree under the supervision of Prof. Hugo Guterman and Rami Hagege. His research interests include real-time light invariant video cameras, underwater color constancy, the use of quaternions in image processing, and application for the theory of relativity in color image processing.