A Vehicle Detection Method in Night Outdoor Scenes Based on Spatio-temporal Bricks

Author

Su, Bailiang ; Li, Chuanzhen ; Wang, Jingling ; Wang, Hui ; Zhang, Qin

Author_Institution

Sch. of Inf. Eng., Commun. Univ. of China, Beijing, China

fYear

2012

fDate

May 30 2012-June 1 2012

Firstpage

337

Lastpage

342

Abstract

A novel approach to detect vehicles in night outdoor scenes is proposed in this paper. By using online subspace learning, the preliminary foreground is obtained based on spatio-temporal bricks. Meanwhile, a new operator named 3DLBP is proposed to describe the local features of bricks. The final foreground is acquired by region-grow with 3DLBP and preliminary foreground. The results of experiment indicate that the proposed approach achieves higher performance in detecting vehicles in night outdoor scenes than common methods.

Keywords

automated highways; learning (artificial intelligence); object detection; object tracking; traffic engineering computing; 3DLBP; intelligent transportation system; night outdoor scenes; online subspace learning; spatio-temporal bricks; vehicle detection method; vehicle tracking; Conferences; Educational institutions; Feature extraction; Lighting; Robustness; Vehicle detection; Vehicles; 3DLBP; region-grow; spatio-temporal bricks; subspace learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Science (ICIS), 2012 IEEE/ACIS 11th International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4673-1536-4

Type

conf

DOI

10.1109/ICIS.2012.24

Filename

6211119