research-article

Research on Vehicle Identification Method Based on Computer Vision

Authors:

Zhou Yan,

Yuan Deming,

Zhou JunAuthors Info & Claims

ICDMML 2019: Proceedings of the 2019 International Conference on Data Mining and Machine Learning

Pages 140 - 145

https://doi.org/10.1145/3335656.3335700

Published: 28 April 2019 Publication History

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Abstract

Identifying the vehicle in front of road is an important research topic for active safety and intelligent driving of vehicles. A vehicle identification algorithm is proposed based on computer vision using supervised machine learning algorithm AdaBoost and Haar-like features. Firstly, in terms of feature selection, dimension reduction processing is performed from two aspects of feature type and feature size, and integral graph is applied to accelerate the calculation of Haar-like eigenvalues. Secondly, a more efficient classifier is constructed based on a small number of effective features, and a single strong classifier is used to identify and verify the vehicle in front. Finally, the whole vehicle identification algorithm is tested with the test data including 350 frames captured from the highway video set and 450 frames captured from the urban road video set. The result shows that the vehicle identification algorithm have a high detection rate and Lower detection error rate.

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Cited By

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Lozano Dominguez JAl-Tam FSanguino TCorreia N(2021)Vehicle Detection System for Smart Crosswalks Using Sensors and Machine Learning2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)10.1109/SSD52085.2021.9429473(984-991)Online publication date: 22-Mar-2021
https://doi.org/10.1109/SSD52085.2021.9429473
Lozano Domínguez JAl-Tam FMateo Sanguino TCorreia N(2020)Analysis of Machine Learning Techniques Applied to Sensory Detection of Vehicles in Intelligent CrosswalksSensors10.3390/s2021601920:21(6019)Online publication date: 23-Oct-2020
https://doi.org/10.3390/s20216019
Rúbio TCruz JJacob JGarrido DCardoso HSilva DRodrigues R(2020)A Semi-automatic Object Identification Technique Combining Computer Vision and Deep Learning for the Crosswalk Detection ProblemIntelligent Data Engineering and Automated Learning – IDEAL 202010.1007/978-3-030-62365-4_59(602-609)Online publication date: 4-Nov-2020
https://dl.acm.org/doi/10.1007/978-3-030-62365-4_59

Index Terms

Research on Vehicle Identification Method Based on Computer Vision
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Matching
        Object identification
        Tracking
      2. Computer vision representations
        Hierarchical representations

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ICDMML 2019: Proceedings of the 2019 International Conference on Data Mining and Machine Learning

April 2019

182 pages

ISBN:9781450360906

DOI:10.1145/3335656

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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International Engineering and Technology Institute, Hong Kong: International Engineering and Technology Institute, Hong Kong

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Published: 28 April 2019

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ICDMML 2019: 2019 International Conference on Data Mining and Machine Learning

April 28 - 30, 2019

Hong Kong, Hong Kong

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Lozano Dominguez JAl-Tam FSanguino TCorreia N(2021)Vehicle Detection System for Smart Crosswalks Using Sensors and Machine Learning2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)10.1109/SSD52085.2021.9429473(984-991)Online publication date: 22-Mar-2021
https://doi.org/10.1109/SSD52085.2021.9429473
Lozano Domínguez JAl-Tam FMateo Sanguino TCorreia N(2020)Analysis of Machine Learning Techniques Applied to Sensory Detection of Vehicles in Intelligent CrosswalksSensors10.3390/s2021601920:21(6019)Online publication date: 23-Oct-2020
https://doi.org/10.3390/s20216019
Rúbio TCruz JJacob JGarrido DCardoso HSilva DRodrigues R(2020)A Semi-automatic Object Identification Technique Combining Computer Vision and Deep Learning for the Crosswalk Detection ProblemIntelligent Data Engineering and Automated Learning – IDEAL 202010.1007/978-3-030-62365-4_59(602-609)Online publication date: 4-Nov-2020
https://dl.acm.org/doi/10.1007/978-3-030-62365-4_59

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Application of Convolutional Neural Network Technology in Vehicle Parking Management

Vehicle Detection and Neural Network Application for Vehicle Classification

Vehicle Detection, Classification and Counting on Highways - Accuracy Enhancements

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