<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

Video-Based Vehicle Detection And Classification In Challenging Scenarios

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Video-Based Vehicle Detection And Classification In Challenging Scenarios"}

In intelligent transportation system, research on vehicle detection and classification has high theory significance and application value. According to the...

Video-Based Vehicle Detection And Classification In Challenging Scenarios

Pubblicato online: 01 set 2014

Pagine: 1077 - 1094

Ricevuto: 28 apr 2014

Accettato: 01 set 2014

DOI: https://doi.org/10.21307/ijssis-2017-695

Parole chiave
Vehicle detection, Gaussian mixture, Bayesian fusion, fuzzy SVM, vehicle classification

© 2014 Yiling Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Video-Based Vehicle Detection And Classification In Challenging Scenarios

Pubblicato online: 01 set 2014

Pagine: 1077 - 1094

Ricevuto: 28 apr 2014

Accettato: 01 set 2014

DOI: https://doi.org/10.21307/ijssis-2017-695

Parole chiaveVehicle detection, Gaussian mixture, Bayesian fusion, fuzzy SVM, vehicle classification

© 2014 Yiling Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
Vehicle detection, Gaussian mixture, Bayesian fusion, fuzzy SVM, vehicle classification