Selecting Local Region Descriptors with a Genetic Algorithm for Real-World Place Recognition

@inproceedings{Trujillo2008SelectingLR,
  title={Selecting Local Region Descriptors with a Genetic Algorithm for Real-World Place Recognition},
  author={Leonardo Trujillo and Gustavo Olague and Francisco Fern{\'a}ndez de Vega and Evelyne Lutton},
  booktitle={EvoWorkshops},
  year={2008}
}
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… 
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Optimization of the hölder image descriptor using a genetic algorithm
TLDR
A local descriptor based on the Hölder exponent, a measure of signal regularity, is studied to find an optimal number of dimensions for the descriptor using a genetic algorithm (GA) to guide the search.
Descriptor Generation and Optimization for a Specific Outdoor Environment
TLDR
A new framework based on the genetic algorithm to create and optimize extensible modular descriptors for specific outdoor environments with improved efficiency and classification performance is investigated.

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