Shape Features of Overlapping Boundary for Classification of Moving Vehicles-Reference-Cited by-同舟云学术

Shape Features of Overlapping Boundary for Classification of Moving Vehicles

Published:2013-01 Issue:1 Volume:3 Page:42-54
ISSN:2155-6997
Container-title:International Journal of Computer Vision and Image Processing
language:en
Short-container-title:

Author:

Dallalzadeh Elham¹,Guru D. S.²

Affiliation:

1. Department of Computer, Islamic Azad University Marvdasht Branch, Marvdasht, Iran

2. Department of Studies in Computer Science, University of Mysore, Mysore, Karnataka, India

Abstract

In this paper, the authors propose a model for classification of moving vehicles in traffic videos. A corner-based tracking method is presented to track and detect moving vehicles. The authors propose to overlap the boundary curves of each of the detected moving vehicles while tracking in a sequence of frames to reconstruct a complete boundary shape of the vehicle. The reconstructed boundary shape is normalized and then shape features are extracted. Vehicles are categorized into 4 different types of vehicle classes using KNN rule, the weighted KNN, PNN, and SVM classifiers. Experiments are conducted on traffic video sequences captured in an uncontrolled environment during daytime.

Publisher

IGI Global

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference22 articles.

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3. Dallalzadeh, E., Guru, D. S., Manjunath, S., & Suraj, M. G. (2011). Corner-based tracking of moving vehicles in traffic videos. In I Proceedings of the 5th Indian International Conference on Artificial Intelligence (pp. 956-969).

4. Dallalzadeh, E., Guru, D. S., Manjunath, S., & Suraj, M. G. (2012). Classification of moving vehicles in traffic videos. In Proceedings of the Second International Conference on Computer Science and Information Technology, 85(2), 221-1, LNICST, Springer.