Result Details

Trajectory classification based on Hidden Markov Models

MLÍCH, J.; CHMELAŘ, P. Trajectory classification based on Hidden Markov Models. Proceedings of 18th International Conference on Computer Graphics and Vision. Moscow: Lomonosov Moscow State University, 2008. p. 101-105. ISBN: 978-5-9556-0112-0.
Type
conference paper
Language
English
Authors
Mlích Jozef, Ing., DCGM (FIT)
Chmelař Petr, Ing., DIFS (FIT)
Abstract

This paper presents a method for statistical modeling and classification of motion trajectories using Hidden Markov Models. Mass recordings from visual surveillance  are processed to extract objects trajectories. Hidden Markov Models of classes of behaviour are created upon some annotated trajectories. In this way, information about complex object behaviour of objects can be discovered.

Additionally, an experiment shows the successful application of Hidden Markov Models on trajectories of people in an underground station in Roma. Finally, a comparison of efficiency on different data sets, is discussed.

Keywords

HMM, Trajectory, Classification

URL
Published
2008
Pages
101–105
Proceedings
Proceedings of 18th International Conference on Computer Graphics and Vision
Conference
GraphiCon'2008
ISBN
978-5-9556-0112-0
Publisher
Lomonosov Moscow State University
Place
Moscow
BibTeX 
@inproceedings{BUT32563,
  author="Jozef {Mlích} and Petr {Chmelař}",
  title="Trajectory classification based on Hidden Markov Models",
  booktitle="Proceedings of 18th International Conference on Computer Graphics and Vision",
  year="2008",
  pages="101--105",
  publisher="Lomonosov Moscow State University",
  address="Moscow",
  isbn="978-5-9556-0112-0",
  url="http://www.graphicon.ru/2008/proceedings/English/S5/Paper_1.pdf"
}
Projects
CARETAKER - Content Analysis and REtrieval Technologies to Apply Knowledge Extraction to massive Recording, EU, Sixth Framework programme, 027231, start: 2006-03-01, end: 2008-09-30, completed
Centre of computer graphics, MŠMT, Centra základního výzkumu, LC06008, start: 2006-03-01, end: 2011-12-31, completed
Research groups
Computer Graphics Research Group (RG GRAPH)
Image and Video Processing Research Group (VZ VIDEO)
Departments
Department of Computer Graphics and Multimedia (DCGM)
Department of Information Systems (DIFS)
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