Car/Non-Car Classification in an Informative Sample Subspace

Author

Fang, Jianzhong ; Qiu, Guoping

Author_Institution

Sch. of Comput. Sci. & Inf. Technol., Nottingham Univ.

Volume

2

fYear

0

fDate

0-0 0

Firstpage

962

Lastpage

965

Abstract

In this paper, we present a method for data classification with application to car/non-car objects. We first developed a sample based car/non-car maximal mutual information low dimensional subspace. We then trained a support vector machine (SVM) in this subspace for the detection of cars. Using publicly available standard training and testing data sets, we demonstrated that our car detector gave very competitive performances

Keywords

automobiles; image classification; object detection; support vector machines; traffic engineering computing; car classification; car detection; car maximal mutual information low dimensional subspace; data classification; informative sample subspace; noncar classification; noncar maximal mutual information low dimensional subspace; support vector machine; Computer science; Image databases; Information technology; Mutual information; Object detection; Performance evaluation; Pixel; Support vector machine classification; Support vector machines; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2006. ICPR 2006. 18th International Conference on

Conference_Location

Hong Kong

ISSN

1051-4651

Print_ISBN

0-7695-2521-0

Type

conf

DOI

10.1109/ICPR.2006.356

Filename

1699366