Use of Stochastic Optimization Algorithms in Image Retrieval Problems

  • Mattia Broilo
  • Francesco G. B. De Natale


In this chapter, the use of stochastic and evolutionary optimization techniques for image retrieval is addressed. We provide background and motivations of such approaches, as well as an overview of some of the most interesting ideas proposed in the recent literature in the field. The relevant methodologies refer to different applications of the optimization process, as a way of either improving the parameter setting in traditional retrieval tools, or directly classifying images within a dataset. Also, the use of stochastic optimization approaches based on social behaviors is discussed, showing how these approaches can be used to capture the semantics of a query through the interaction with the user. Strengths and weaknesses of different solutions are discussed, taking into account also implementation issues, complexity, and open directions of the research.


Particle Swarm Optimization Fitness Function Image Retrieval Particle Swarm Optimization Algorithm Stochastic Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.DISIUniversity of TrentoTrentoItaly

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