An efficient optimizer for simple point process models

Ahmed Gamal-Eldin; Guillaume Charpiat; Xavier Descombes; Josiane Zerubia

doi:10.1117/12.2009238

14 February 2013 An efficient optimizer for simple point process models

Ahmed Gamal-Eldin, Guillaume Charpiat, Xavier Descombes, Josiane Zerubia

Proceedings Volume 8657, Computational Imaging XI; 86570M (2013) https://doi.org/10.1117/12.2009238
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

In this paper we discuss the main characteristics (that we consider to be essential) for the design of an efficient optimizer in the context of highly non-convex functions. We consider a specific model known as Marked Point Process (MPP). Given that the probability density is multimodal, and given the size of the configuration space, an exploration phase is essential at the beginning of the algorithm. Next, the fine details of the density function should be discovered. We propose efficient kernels to efficiently explore the different modes of the density, and other kernels to discover the details of each mode. We study the algorithm theoretically to express convergence speeds and to select its best parameters. We also present a simple and generic method to parallelize the optimization of a specific class of MPP models. We validate our ideas first on synthetic data of configurations of different sizes to prove the efficiency of the proposed kernels. Finally we present results on three different applications.

Citation Download Citation

Ahmed Gamal-Eldin, Guillaume Charpiat, Xavier Descombes, and Josiane Zerubia "An efficient optimizer for simple point process models", Proc. SPIE 8657, Computational Imaging XI, 86570M (14 February 2013); https://doi.org/10.1117/12.2009238

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available