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Swarm-Based Methods Applied to Computer Vision

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Smart Computer Vision

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

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Abstract

Swarm-based algorithms are nature-inspired methods that have been applied to solve complex problems. They are population-based methods that attempt to imitate the behaviors observed in natural systems that allow said systems to solve problems. These methods consider a set of individuals that can perform very simple operations when operating independently, but can solve complex problems when viewed as a set operating in parallel. Another important feature of these methods is that they do not have a central control, since all the individuals have the same importance in the system and perform the same operations. Multiple swarm-based methods have been developed over the years, and they have been applied to solve a wide variety of problems. Among others, these methods have been successfully used to solve various machine vision tasks. This chapter shows an overview of the main swarm-based solutions proposed to solve problems related to computer vision. The chapter begins by presenting a brief description of the principles behind swarm algorithms, as well as the basic operations of swarm methods that have been applied in computer vision. After this, the particularities of the swarm-based algorithms that make them useful for solving complex problems are discussed. Then, the remainder of the chapter is devoted to showing the applications of these methods to various problems and subproblems related to computer vision.

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  1. University of Salamanca, Escuela Politécnica Superior de Zamora, Zamora, Spain

    María-Luisa Pérez-Delgado

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  2. Thiruvettakudy, National Institute of Technology, Puducherry, Karaikal, India

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    B. Surendiran

  4. University of North Texas, Denton, TX, USA

    Junhua Ding

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Pérez-Delgado, ML. (2023). Swarm-Based Methods Applied to Computer Vision. In: Kumar, B.V., Sivakumar, P., Surendiran, B., Ding, J. (eds) Smart Computer Vision. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-20541-5_16

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