Paper
5 March 2014 Modelling dynamics with context-free grammars
Juan-M. García-Huerta, Hugo Jiménez-Hernández, Ana-M. Herrera-Navarro, Teresa Hernández-Díaz, Ivan Terol-Villalobos
Author Affiliations +
Proceedings Volume 9026, Video Surveillance and Transportation Imaging Applications 2014; 902611 (2014) https://doi.org/10.1117/12.2040973
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
This article presents a strategy to model the dynamics performed by vehicles in a freeway. The proposal consists on encode the movement as a set of finite states. A watershed-based segmentation is used to localize regions with high-probability of motion. Each state represents a proportion of a camera projection in a two-dimensional space, where each state is associated to a symbol, such that any combination of symbols is expressed as a language. Starting from a sequence of symbols through a linear algorithm a free-context grammar is inferred. This grammar represents a hierarchical view of common sequences observed into the scene. Most probable grammar rules express common rules associated to normal movement behavior. Less probable rules express themselves a way to quantify non-common behaviors and they might need more attention. Finally, all sequences of symbols that does not match with the grammar rules, may express itself uncommon behaviors (abnormal). The grammar inference is built with several sequences of images taken from a freeway. Testing process uses the sequence of symbols emitted by the scenario, matching the grammar rules with common freeway behaviors. The process of detect abnormal/normal behaviors is managed as the task of verify if any word generated by the scenario is recognized by the grammar.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juan-M. García-Huerta, Hugo Jiménez-Hernández, Ana-M. Herrera-Navarro, Teresa Hernández-Díaz, and Ivan Terol-Villalobos "Modelling dynamics with context-free grammars", Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 902611 (5 March 2014); https://doi.org/10.1117/12.2040973
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Cited by 2 scholarly publications.
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KEYWORDS
Motion models

Motion detection

Cameras

Image segmentation

Modeling

Visualization

Sensors

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