Feature representation and extraction for image search and video retrieval

Document Type

Syllabus

Publication Date

1-1-2017

Abstract

The ever-increasing popularity of intelligent image search and video retrieval warrants a comprehensive study of the major feature representation and extraction methods often applied in image search and video retrieval. Towards that end, this chapter reviews some representative feature representation and extraction approaches, such as the Spatial Pyramid Matching (SPM), the soft assignment coding, the Fisher vector coding, the sparse coding and its variants, the Local Binary Pattern (LBP), the Feature Local Binary Patterns (FLBP), the Local Quaternary Patterns (LQP), the Feature Local Quaternary Patterns (FLQP), the Scale-invariant feature transform (SIFT), and the SIFT variants, which are broadly applied in intelligent image search and video retrieval.

Identifier

85018481816 (Scopus)

Publication Title

Intelligent Systems Reference Library

External Full Text Location

https://doi.org/10.1007/978-3-319-52081-0_1

e-ISSN

18684408

ISSN

18684394

First Page

1

Last Page

19

Volume

121

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