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Feature Selection

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Computer Vision

Synonyms

Dimensionality reduction; Feature reduction; Variable selection

Related Concepts

Definition

Feature selection refers to a set of techniques for automatically extracting important features from raw observations or reducing the set of dimensions from a given feature set, in a task-dependent manner.

Background

Feature selection refers to a large set of overlapping techniques, ranging from methods such as dimensionality reduction, subset selection, and more recently feature learning or representation learning. Since early works in pattern analysis [1], there has been an interest in extracting parsimonious and meaningful features from raw data for tasks such as recognition, compression, etc. Classically, features based on intuition or domain knowledge were considered popular; however, automatic methods for feature selection that can find optimal transformations of raw data are of contemporary interest. Toward this, linear and...

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Author information

Authors and Affiliations

  1. University of Maryland, College Park, MD, USA

    Rama Chellappa

  2. Arizona State University, Tempe, AZ, USA

    Pavan Turaga

Authors
  1. Rama Chellappa
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  2. Pavan Turaga
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Corresponding author

Correspondence to Pavan Turaga .

Section Editor information

  1. University of Maryland, College Park, United States

    Rama Chellappa

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Chellappa, R., Turaga, P. (2020). Feature Selection. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-03243-2_299-1

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  • DOI: https://doi.org/10.1007/978-3-030-03243-2_299-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03243-2

  • Online ISBN: 978-3-030-03243-2

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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