Vehicle Make and Model Classification System using Bag of SIFT Features

被引：0

作者：

Manzoor, Muhammad Asif ^{[1
]}

Morgan, Yasser ^{[1
]}

机构：

[1] Univ Regina, Fac Engn & Appl Sci, Regina, SK, Canada

来源：

2017 IEEE 7TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE IEEE CCWC-2017 | 2017年

关键词：

Vehicle Classification; Support Vector Machine; Bag of Words Model; Scale Invariant Transform Feature (SIFT);

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Vehicle Make and Model classification is an important part of Intelligent Transportation System. In this work, we have proposed a method based on Linear Support vector machine to solve this problem. Scale Invariant Transform Feature (SIFT) algorithm is used in this work to extract and represent local interest points. Bag of words model is used to represent the local features as fixed length vector to represent an image. The proposed method is evaluated on a publicly available vehicle make and model dataset and promising results are achieved with this method.

引用

页数：5

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