Selecting local region descriptors with a genetic algorithm for real-world place recognition

Published in Conferences Papers
  1. Leonardo Trujillo, Gustavo Olague, Francisco Fernández Vega and Evelyne Lutton. Selecting Local Region Descriptors with a Genetic Algorithm for Real-World Place Recognition. In EvoWorkshops. 2008, 325-334. BibTeX

    @inproceedings{DBLP:conf/evoW/TrujilloOVL08,
    	author = "Leonardo Trujillo and Gustavo Olague and Francisco Fern{\'a}ndez de Vega and Evelyne Lutton",
    	title = "Selecting Local Region Descriptors with a Genetic Algorithm for Real-World Place Recognition",
    	booktitle = "EvoWorkshops",
    	year = 2008,
    	pages = "325-334",
    	ee = "http://dx.doi.org/10.1007/978-3-540-78761-7_33",
    	crossref = "DBLP:conf/evoW/2008",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    
  2. Mario Giacobini, Anthony Brabazon, Stefano Cagnoni, Gianni Di Caro, Rolf Drechsler, Anikó Ekárt, Anna Esparcia-Alcázar, Muddassar Farooq, Andreas Fink, Jon McCormack, Michael O'Neill, Juan Romero, Franz Rothlauf, Giovanni Squillero, Sima Uyar and Shengxiang Yang (eds.). Applications of Evolutionary Computing, EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008. Proceedings 4974. Springer, 2008. BibTeX

    @proceedings{DBLP:conf/evoW/2008,
    	editor = "Mario Giacobini and Anthony Brabazon and Stefano Cagnoni and Gianni Di Caro and Rolf Drechsler and Anik{\'o} Ek{\'a}rt and Anna Esparcia-Alc{\'a}zar and Muddassar Farooq and Andreas Fink and Jon McCormack and Michael O'Neill and Juan Romero and Franz Rothlauf and Giovanni Squillero and Sima Uyar and Shengxiang Yang",
    	title = "Applications of Evolutionary Computing, EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008. Proceedings",
    	booktitle = "EvoWorkshops",
    	publisher = "Springer",
    	series = "Lecture Notes in Computer Science",
    	volume = 4974,
    	year = 2008,
    	isbn = "978-3-540-78760-0",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    
Abstract

The basic problem for a mobile vision system is determining where it is located within the world. In this paper, a recognition system is presented that is capable of identifying known places such as rooms and corridors. The system relies on a bag of features approach using locally prominent image regions. Real-world locations are modeled using a mixture of Gaussians representation, thus allowing for a multimodal scene characterization. Local regions are represented by a set of 108 statistical descriptors computed from different modes of information. From this set the system needs to determine which subset of descriptors captures regularities between image regions of the same location, and also discriminates between regions of different places. A genetic algorithm is used to solve this selection task, using a fitness measure that promotes: 1) a high classification accuracy; 2) the selection of a minimal subset of descriptors; and 3) a high separation among place models. The approach is tested on two real world examples: a) using a sequence of still images with 4 different locations; and b) a sequence that contains 8 different locations. Results confirm the ability of the system to identify previously seen places in a real-world setting.

Published in
10th European Workshop on Evolutionary Computation in Image Analysis and Signal Processing (EvoASP'08)
Volume 4974
Pages 325-334
http://link.springer.com/chapter/10.1007%2F978-3-540-78761-7_33
Date of conference
24 - 26 March 2008
ISSN
0302-9743
ISBN
978-3-540-78761-7

 

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