NDLI: Traffic accident risk analysis based on relation of Common Route Models

Content Provider	IEEE Xplore Digital Library
Author	Er, U. Yuksel, S. Akoz, O. Karsligil, M.E.
Copyright Year	2012
Description	Author affiliation: Yildiz Technical University (Er, U.; Yuksel, S.; Akoz, O.; Karsligil, M.E.)
Abstract	This paper proposes a novel accident prediction approach based on extracting the relation between interested vehicles and increasing risk factor according to anomaly detection in real time traffic videos. In learning process of the traffic model at intersections, we detect all trajectories by tracking of each vehicle and then group them considering road model. All trajectories are clustered by Continuous Hidden Markov Model with Mixture of Gaussian (MoG) and Common Route Model (CRM) for each group of trajectories is found. After extracting all CRM's and defining their relations, in real time traffic analysis process, partial motion of the vehicles are evaluated and anomalies are detected if there is. In this approach, while searching for accident risk, partial trajectories of vehicles are classified to the most similar CRM's. For each source vehicle, risk factors are calculated with target vehicles that are in related CRM's and has Region of Interest (ROI) intersected with source vehicle. The advantage of this approach is that the system does only analyze vehicles in accident risk and this increases the performance of the system. Beside these, since CRM information and their features like relations, directions and likelihood in classification process are learned, anomalies can easily be detected and used as risk enhancer. Experimental results show that the proposed model has high prediction rate in real world accident events.
Starting Page	2561
Ending Page	2564
File Size	802671
Page Count	4
File Format	PDF
ISBN	9781467322164
ISSN	10514651
e-ISBN	9784990644109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-11
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	ICPR Org Committee
Subject Keyword	Vehicles Accidents Trajectory Hidden Markov models Customer relationship management Videos Real-time systems
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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