A State-Based Language for Enhanced Video Surveillance Modeling (SEL)

SEL, a State-based Language for Video Surveillance Modeling, is a formal language designed to represent and identify activities in surveillance systems through scenario semantics and the creation of motion primitives structured in programs. Motion primitives represent the temporal evolution of motio...

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Published inModelling Vol. 5; no. 2; pp. 549 - 568
Main Authors Ramirez-Rosales, Selene, Diaz-Jimenez, Luis-Antonio, Canton-Enriquez, Daniel, Perez-Ramos, Jorge-Luis, Hernandez-Ramirez, Herlindo, Herrera-Navarro, Ana-Marcela, Xicotencatl-Ramirez, Gabriela, Jimenez-Hernandez, Hugo
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.06.2024
Subjects
Algorithms
Artificial intelligence
Deep learning
event description language
Evolution
formal language
Grammar
inference of activities
Interactive learning
Language
Modelling
motion primitives
Neural networks
Semantics
Surveillance
surveillance system
Surveillance systems
Synchronism
Syntax
Variables
Vision systems
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Abstract SEL, a State-based Language for Video Surveillance Modeling, is a formal language designed to represent and identify activities in surveillance systems through scenario semantics and the creation of motion primitives structured in programs. Motion primitives represent the temporal evolution of motion evidence. They are the most basic motion structures detected as motion evidence, including operators such as sequence, parallel, and concurrency, which indicate trajectory evolution, simultaneity, and synchronization. SEL is a very expressive language that characterizes interactions by describing the relationships between motion primitives. These interactions determine the scenario’s activity and meaning. An experimental model is constructed to demonstrate the value of SEL, incorporating challenging activities in surveillance systems. This approach assesses the language’s suitability for describing complicated tasks.
AbstractList SEL, a State-based Language for Video Surveillance Modeling, is a formal language designed to represent and identify activities in surveillance systems through scenario semantics and the creation of motion primitives structured in programs. Motion primitives represent the temporal evolution of motion evidence. They are the most basic motion structures detected as motion evidence, including operators such as sequence, parallel, and concurrency, which indicate trajectory evolution, simultaneity, and synchronization. SEL is a very expressive language that characterizes interactions by describing the relationships between motion primitives. These interactions determine the scenario’s activity and meaning. An experimental model is constructed to demonstrate the value of SEL, incorporating challenging activities in surveillance systems. This approach assesses the language’s suitability for describing complicated tasks.
Author Ramirez-Rosales, Selene
Diaz-Jimenez, Luis-Antonio
Canton-Enriquez, Daniel
Perez-Ramos, Jorge-Luis
Hernandez-Ramirez, Herlindo
Xicotencatl-Ramirez, Gabriela
Herrera-Navarro, Ana-Marcela
Jimenez-Hernandez, Hugo
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  surname: Jimenez-Hernandez
  fullname: Jimenez-Hernandez, Hugo
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Snippet SEL, a State-based Language for Video Surveillance Modeling, is a formal language designed to represent and identify activities in surveillance systems through...
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SubjectTerms Algorithms
Artificial intelligence
Deep learning
event description language
Evolution
formal language
Grammar
inference of activities
Interactive learning
Language
Modelling
motion primitives
Neural networks
Semantics
Surveillance
surveillance system
Surveillance systems
Synchronism
Syntax
Variables
Vision systems
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