Automatic accident detection using topic models

Automatic accident detection is one of the most important tasks for an intelligent transportation system (ITS). In this paper, a new framework for automated traffic accident recognition using topic models is proposed. This framework uses a set of visual features and automatically discovers the motio...

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Bibliographic Details
Main Authors: Kaviani, Razie, Ahmadi, Parvin, Gholampour, Iman
Format: Conference Proceeding
Language:English
Subjects:
Accidents
Electrical engineering
Feature extraction
Hidden Markov models
Intelligent transportation system
topic model
Tracking
traffic accident detection
Trajectory
Visualization
Online Access:Request full text
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Summary:Automatic accident detection is one of the most important tasks for an intelligent transportation system (ITS). In this paper, a new framework for automated traffic accident recognition using topic models is proposed. This framework uses a set of visual features and automatically discovers the motion patterns in traffic scenes. Then, using these learned motion patterns, occurrence of an accident could be detected by various abnormality measures. Results on real video sequences collected from Tehran traffic control center confirm the effectiveness and the applicability of the proposed framework.
ISSN:2164-7054
DOI:10.1109/IranianCEE.2015.7146256