VIDEO-BASED VEHICLE DETECTION AND CLASSIFICATION IN CHALLENGING SCENARIOS   

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

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VOLUME 7 , ISSUE 3 (September 2014) > List of articles

 VIDEO-BASED VEHICLE DETECTION AND CLASSIFICATION IN CHALLENGING SCENARIOS   

Yiling Chen * / GuoFeng Qin *

Keywords : Vehicle detection, Gaussian mixture, Bayesian fusion, fuzzy SVM, vehicle classification.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 3, Pages 1,077-1,094, DOI: https://doi.org/10.21307/ijssis-2017-695

License : (CC BY-NC-ND 4.0)

Received Date : 28-April-2014 / Accepted: 15-July-2014 / Published Online: 01-September-2014

ARTICLE

ABSTRACT

Abstract- In intelligent transportation system, research on vehicle detection and classification has high theory significance and application value. According to the traditional methods of vehicle detection which can’t be well applied in challenging scenario, this paper proposes a novel Bayesian fusion algorithm based on Gaussian mixture model. We extract the features of vehicle from images, including shape features, texture features, and the gradient direction histogram features after dimension reduction. In vehicle classification part, we adopt fuzzy support vector machine, and design a novel vehicle classifier based on nested one-vs-one algorithm. Finally, experimental tests show excellent results of our methods in both vehicle detection and classification.   

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