3D Otsu Moving Vehicle Detection Method Based on Steepest Ascent

Author

Shangwan Chen ; Zhengjie Wan

Author_Institution

Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China

fYear

2013

fDate

21-23 June 2013

Firstpage

1040

Lastpage

1043

Abstract

In the outdoor traffic situation the large number of noise can be eliminated by using traditional three-dimensional (3D) Otsu method, but the work is time-consuming and can not satisfy the real-time demand. To solve this problem, a method for 3D Otsu moving vehicle detection based on steepest ascent is proposed which combines with Mixture Gaussian Backround Modeling (MGBM). Experimental results show that it can detect moving cars accurately for real-time video processing in the case of complex backgrounds and jittering in the video.

Keywords

Gaussian processes; gradient methods; object detection; road traffic; road vehicles; traffic engineering computing; video signal processing; 3D Otsu moving vehicle detection method; MGBM; mixture Gaussian background modeling; outdoor traffic situation; real-time video processing; steepest ascent method; three-dimensional Otsu method; Histograms; Image segmentation; Object detection; Real-time systems; Three-dimensional displays; Vectors; Vehicle detection; Mixture Gaussian Background Modeling method; moving objects detection; three-dimensional Otsu method; video frame;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on

Conference_Location

Shiyang

Type

conf

DOI

10.1109/ICCIS.2013.278

Filename

6643194