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Syntactic Pattern Recognition in Computer Vision: A Systematic Review

delete2021-04-17
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PRE
AI
G
Gilberto Astolfi *
F
Fábio Prestes Cesar Rezende
J
João Vitor de Andrade Porto
E
Edson Takashi Matsubara
H
Hemerson Pistori
DOI:10.1145/3447241delete
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摘要

摘要

En 中文
Using techniques derived from the syntactic methods for visual pattern recognition is not new and was much explored in the area called syntactical or structural pattern recognition. Syntactic methods have been useful because they are intuitively simple to understand and have transparent, interpretable, and elegant representations. Their capacity to represent patterns in a semantic, hierarchical, compositional, spatial, and temporal way have made them very popular in the research community. In this article, we try to give an overview of how syntactic methods have been employed for computer vision tasks. We conduct a systematic literature review to survey the most relevant studies that use syntactic methods for pattern recognition tasks in images and videos. Our search returned 597 papers, of which 71 papers were selected for analysis. The results indicated that in most of the studies surveyed, the syntactic methods were used as a high-level structure that makes the hierarchical or semantic relationship among objects or actions to perform the most diverse tasks.
Keyword:
Computer vision
image representation
formal languages
syntacticmethods
pattern recognition
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ACM Computing Surveys 封面图
ACM Computing Surveys
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28
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2.4K
被引数:
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Universidade Federal de Mato Grosso do Sul 封面图
Universidade Federal de Mato Grosso do Sul
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被引数: 2.1K
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