Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost

This paper presents the implementation and comparison of algorithms for support vector machines “SVM” and AdaBoost in the classification of public and private vehicles using segmented images of video sequences taken in Bogotá city. Using as tools the OpenCV libraries implemented in C. The algorithms...

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Main Authors: Calderon, Francisco, Parra, Carlos Alberto
Format: Digital
Language:spa
Published: UNIVERSIDAD ANTONIO NARIÑO 2013
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Online Access:https://revistas.uan.edu.co/index.php/ingeuan/article/view/348
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author Calderon, Francisco
Parra, Carlos Alberto
author_facet Calderon, Francisco
Parra, Carlos Alberto
author_sort Calderon, Francisco
collection OJS
description This paper presents the implementation and comparison of algorithms for support vector machines “SVM” and AdaBoost in the classification of public and private vehicles using segmented images of video sequences taken in Bogotá city. Using as tools the OpenCV libraries implemented in C. The algorithms performances are remarkable and therefore its use could have a positive impact in the reduction of traffic problems.
format Digital
id revistas.uan.edu.co-article-348
institution Revista INGE@UAN
language spa
publishDate 2013
publisher UNIVERSIDAD ANTONIO NARIÑO
record_format ojs
spelling revistas.uan.edu.co-article-3482021-02-16T16:53:46Z Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost Calderon, Francisco Parra, Carlos Alberto AdaBosst árboles binarios OpenCV reconocimiento de patrones SVM Ingeniería de tráfico clasificación de vehículos AdaBoost Binary Trees OpenCV Pattern recognition SVM Traffic engineering Vehicles classification This paper presents the implementation and comparison of algorithms for support vector machines “SVM” and AdaBoost in the classification of public and private vehicles using segmented images of video sequences taken in Bogotá city. Using as tools the OpenCV libraries implemented in C. The algorithms performances are remarkable and therefore its use could have a positive impact in the reduction of traffic problems. Este artículo presenta el diseño e implementación y comparación de algoritmos para la clasificación de vehículos privados y públicos en Bogotá. El desempeño de estos algoritmos de clasificación es notable, y vale la pena anotar el impacto potencial que tendrían en la reducción de problemas de tráfico. Los datos experimentales fueron imágenes segmentadas de vídeos tomados sobre el tráfico en la ciudad de Bogotá. Por otro lado, los algoritmos que se utilizaron son máquinas de aprendizaje como Support Vector Machines “SVM” y Adaboost. Vale la pena notar, que se hizo uso de las librerías OpenCV implementadas en C. UNIVERSIDAD ANTONIO NARIÑO 2013-09-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.uan.edu.co/index.php/ingeuan/article/view/348 INGE@UAN - TENDENCIAS EN LA INGENIERÍA; Vol. 3 Núm. 5 (2012) 2346-1446 2145-0935 spa https://revistas.uan.edu.co/index.php/ingeuan/article/view/348/290 https://creativecommons.org/licenses/by-nc-sa/4.0
spellingShingle AdaBosst
árboles binarios
OpenCV
reconocimiento de patrones
SVM
Ingeniería de tráfico
clasificación de vehículos
AdaBoost
Binary Trees
OpenCV
Pattern recognition
SVM
Traffic engineering
Vehicles classification
Calderon, Francisco
Parra, Carlos Alberto
Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_full Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_fullStr Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_full_unstemmed Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_short Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_sort public and private service vehicle classification in bogota using svm and adaboost
topic AdaBosst
árboles binarios
OpenCV
reconocimiento de patrones
SVM
Ingeniería de tráfico
clasificación de vehículos
AdaBoost
Binary Trees
OpenCV
Pattern recognition
SVM
Traffic engineering
Vehicles classification
topic_facet AdaBosst
árboles binarios
OpenCV
reconocimiento de patrones
SVM
Ingeniería de tráfico
clasificación de vehículos
AdaBoost
Binary Trees
OpenCV
Pattern recognition
SVM
Traffic engineering
Vehicles classification
url https://revistas.uan.edu.co/index.php/ingeuan/article/view/348
work_keys_str_mv AT calderonfrancisco publicandprivateservicevehicleclassificationinbogotausingsvmandadaboost
AT parracarlosalberto publicandprivateservicevehicleclassificationinbogotausingsvmandadaboost
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