Motion pattern analysis using partial trajectories for abnormal movement detection in crowded scenes

G. T. Bae, S. Y. Kwak, H. R. Byun

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

A motion pattern analysis method for abnormal movement detection is introduced. It analyses motion patterns and detects abnormal movement using partial trajectories, which can be obtained in crowded scenes and are more effective than local motion. In addition, the proposed method is able to deal with noisy data, which is a major cause of false alarms. The experimental results from real-world traffic scene datasets show that the proposed method improves on previous, local motion-based methods.

Original languageEnglish
Pages (from-to)186-187
Number of pages2
JournalElectronics Letters
Volume49
Issue number3
DOIs
Publication statusPublished - 2013 Jan 31

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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abstract = "A motion pattern analysis method for abnormal movement detection is introduced. It analyses motion patterns and detects abnormal movement using partial trajectories, which can be obtained in crowded scenes and are more effective than local motion. In addition, the proposed method is able to deal with noisy data, which is a major cause of false alarms. The experimental results from real-world traffic scene datasets show that the proposed method improves on previous, local motion-based methods.",
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Motion pattern analysis using partial trajectories for abnormal movement detection in crowded scenes. / Bae, G. T.; Kwak, S. Y.; Byun, H. R.

In: Electronics Letters, Vol. 49, No. 3, 31.01.2013, p. 186-187.

Research output: Contribution to journalArticle

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AU - Byun, H. R.

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N2 - A motion pattern analysis method for abnormal movement detection is introduced. It analyses motion patterns and detects abnormal movement using partial trajectories, which can be obtained in crowded scenes and are more effective than local motion. In addition, the proposed method is able to deal with noisy data, which is a major cause of false alarms. The experimental results from real-world traffic scene datasets show that the proposed method improves on previous, local motion-based methods.

AB - A motion pattern analysis method for abnormal movement detection is introduced. It analyses motion patterns and detects abnormal movement using partial trajectories, which can be obtained in crowded scenes and are more effective than local motion. In addition, the proposed method is able to deal with noisy data, which is a major cause of false alarms. The experimental results from real-world traffic scene datasets show that the proposed method improves on previous, local motion-based methods.

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