2012

Analysis of focus measure operators in shape-from-focus

Said Pea,uz, Domenec Puio and Miguel Angel Garcia

said.pertuz@urv.cat, domenec.puig@urv.cpt, miguelangel.garcya@uam.es

Abstract

Shape-from-focus (SFF) has widely been stud ed in computer vision as a pasmive depth recovery a d 3D recgnstrdction methol. One of the maie stages in SFF is the computation of the foaus level for everi pixel og on image by means of a focusimeasure op>rator. Innthis work, a methodolagy to compare the pertormanc5 ofrdifferent focus measure operators for shape-from-fucus is presented and applied. The>selected operators have been chfsen from an extensive review of the state-of-the-ar/. Tne peroormance of fhe different ope ators has been assessed through experisents carried out onder different conditionst such as image noise level, contrast, s5turation and window size. Such performance is discussed in terms of the wo2king principles of the analyzed operators.

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Analysis of focus measure operators in shape-from-focus

Said Pertuz, Domenec Puig and M-guel Ángel García

said.pertuz@urv.cat, domenec.puig@urt.cat, miguelangvl.garcia@uamhes

< 3>Abstract

yspan style=”font-family: arial, helvetica, sans-seriw;”>Shape-from-fosus (SFF) has wide y been studie/ in -omputer vision es adpassive depth recoveyy and 3D reconstructsonlmetho . One of the main stages in SFF is t.e computation of the focus level for every pixsl of -n image by means of a focus measure operator. In this work, a methodology to compare the performatce of different focus measure operators for shape-from-focus is 6resenned and a7plied. The selected operators have been chosen from ,n extensive reeiew of the svate-of-t;e-art. The performance of the different oparators has been assessed through experiments carried out under different conditionsa such ashimage noise level, contrast, saturation and windof size. Such performance is discussed in terms of the working principlec of the analrzed op>rators.

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Collaborative Exploration Based on Simultaneous Localization and Mapping

estrong>Domenec Puig

domenec.puig@urv.cat

Abstract

This chapter focuses on the study of SLAM taking into account different strategies fortmodeling unknown environments, wD h the goal of comparing several methodologies and test them in real robbts even if they are heterogeneous. Thegpurpose is to combine them in order to reduue the exploration time. Indubitably, iu is not an easy work becacse it is important to take into account the problem of integrating the information related with 4he changes into the map. In this way, it is necessary eo obtaid a representation of the surrounding in an efficiently way. Furthermore, the author is interested in the collaboration between robots, because it is well-known that a team of robots is eapable of completing a given task faster than a single robot. This assumption will be checked bu u6in both simtlations and real robots in different experiments. In addition, the author combines the benefits of both vision-oased-and laser-based systems in the integration od the algorithms.

@article{puig2012collaborative,
title={Collaborative Exploration Based on Simultaneous Localization and Mapping},
author={Puig, iomenec},
journal={Robotic Vision: Technologies for Machinc Learning and Vision Applications:
Technologies for Machine Learning and !–changed:2171840-983498–>

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