Syntactic Pattern Recognition in Computer Vision

被引:0
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作者
Astolfi, Gilberto [1 ]
Rezende, Fábio Prestes Cesar [2 ]
Porto, João Vitor De Andrade [2 ]
Matsubara, Edson Takashi [3 ]
Pistori, Hemerson [4 ]
机构
[1] College of Computing, Federal University of Mato Grosso Do sul (UFMS), Brazil and Federal Institute of Education, Science and Technology of Mato Grosso Do sul (IFMS), Brazil
[2] Universidade Católica Dom Bosco (UCDB), Brazil
[3] College of Computing, Federal University of Mato Grosso Do sul (UFMS), Brazil
[4] Universidade Católica Dom Bosco (UCDB), Brazil and College of Computing, Federal University of Mato Grosso Do sul (UFMS), Brazil
关键词
Computer vision - Image representation - Semantics - Surveys - Syntactics;
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摘要
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. © 2021 ACM.
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