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Importance Sampling via Load-Balanced Facility Location
 

Summary: Importance Sampling via
Load-Balanced Facility Location
Aaron Archer and Shankar Krishnan
AT&T Labs--Research, 180 Park Avenue, Florham Park, NJ 07932.
{aarcher,krishnas}@research.att.com
Abstract. In this paper, we consider the problem of "importance sampling" from
a high dynamic range image, motivated by a computer graphics problem called
image-based lighting. Image-based lighting is a method to light a scene by using
real-world images as part of a 3D environment. Intuitively, the sampling problem
reduces to finding representative points from the image such that they have higher
density in regions of high intensity (or energy) and low density in regions of low
intensity (or energy).
We formulate this task as a facility location problem where the facility costs are
a function of the demand served. In particular, we aim to encourage load balance
amongst the facilities by using V-shaped facility costs that achieve a minimum
at the "ideal" level of demand. We call this the load-balanced facility location
problem, and it is a generalization of the uncapacitated facility location problem
with uniform facility costs. We develop a primal-dual approximation algorithm
for this problem, and analyze its approximation ratio using dual fitting and factor-
revealing linear programs. We also give some experimental results from applying

  

Source: Archer, Aaron - Algorithms and Optimization Group, AT&T Labs-Research

 

Collections: Computer Technologies and Information Sciences