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

共 50 条

[41] Classification of Magnetic Resonance Images using Bag of Features for Detecting Dementia
Bansal, Deepika
Khanna, Kavita
Chhikara, Rita
Dua, Rakesh Kumar
Malhotra, Rajeev
INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE, 2020, 167 : 131 - 137
[42] Time-series Classification Using Neural Bag-of-Features
Passalis, Nikolaos
Tsantekidis, Avraam
Tefas, Anastasios
Kanniainen, Juho
Gabbouj, Moncef
Iosifidis, Alexandros
2017 25TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2017, : 301 - 305
[43] Classification of Temporal and Sequential Data using Bag-of-subsequences Features
Ando, Shin
Suka, Yutaro
2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW), 2015, : 1417 - 1424
[44] Vehicle Subtype, Make and Model Classification from Side Profile Video
Boyle, Jonathan
Ferryman, James
2015 12TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE (AVSS), 2015,
[45] Bag of Visual Words Model with Deep Spatial Features for Geographical Scene Classification
Feng, Jiangfan
Liu, Yuanyuan
Wu, Lin
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2017, 2017
[46] Vehicle Attribute Recognition by Appearance: Computer Vision Methods for Vehicle Type, Make and Model Classification
Ni, Xingyang
Huttunen, Heikki
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2021, 93 (04): : 357 - 368
[47] Vehicle Attribute Recognition by Appearance: Computer Vision Methods for Vehicle Type, Make and Model Classification
Xingyang Ni
Heikki Huttunen
Journal of Signal Processing Systems, 2021, 93 : 357 - 368
[48] Vehicle Make and Model Recognition Using Symmetrical SURF
Hsieh, Jun-Wei
Chen, Li-Chih
Chen, Duan-Yu
Cheng, Shyi-Chyi
2013 10TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE (AVSS 2013), 2013, : 472 - 477
[49] A system for vehicle recognition in video based on SIFT features, mixture models, and support vector machines
Nag, Abhikesh
Miller, David J.
Brown, Andrew P.
Sullivan, Kevin J.
INTELLIGENT COMPUTING: THEORY AND APPLICATIONS V, 2007, 6560
[50] TONE-MAPPING FOR AN HDR SURVEILLANCE SYSTEM USING SIFT FEATURES
Jinno, Takao
Kuriyama, Shigeru
Okuda, Masahiro
2013 PROCEEDINGS OF THE 21ST EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2013,

← 1 2 3 4 5 →