[Brown CS Talks] Brown CS Seminar: Assaf Zomet in Lubrano on December 6, 2002 at 11 am

[talks@list.cs.brown.edu]

			       Seminar
		  
		  The Department of Computer Science
			   BROWN UNIVERSITY

			      
			       presents

			     Assaf Zomet
		   
	      School of Computer Science and Engineering
		  The Hebrew University of Jerusalem

						     
		  Friday, December 6, 2002 at  11 am

		       Room 506 (CIT 5th floor)

	       Refreshments will be served at 10:45 am
 

		 Learning to separate transparencies
			       
			       
			       Abstract

Understanding a viewed scene from images is challenging. It may require
segmenting the images to objects, estimating the geometry and color of
the 
scene, etc.

The talk will start by presenting some examples for vision tasks which
may be solved by scene understanding. It will be shown that such tasks
can be approached even without understanding of the viewed scene;
low-level statistics or reasonable approximations can be used instead.

The main presented task will be separation of transparent layers: How
to separate a single image consisting of two super-positioned layers
into the two layers.

Certain simple images are known to trigger a percept of transparency:
The input image $I$ is perceived as the sum of two images
$I(x,y)=I_1(x,y)+I_2(x,y)$. We will present a model for choosing the
``best'' decomposition from the infinite number of ways to express $I$
as a sum of two images.

We suggest that transparency is the rational percept of a system that
is adapted to the statistics of natural scenes. We present a
probabilistic model of images based on the qualitative statistics of
derivative filters and ``corner detectors'' in natural scenes and use
this model to find the most probable decomposition of a novel
image. The optimization is performed using loopy belief propagation.
We show that our model computes perceptually ``correct'' decompositions
on real and synthetic images.

The talk includes works done with: Anat Levin, Yair Weiss, Shmuel
Peleg, Daphna Weinshall, Doron Feldman and Alex Rav-Acha.


		    Host:  Professor Michael Black