Automatic Object Tracking Using Edge Orientation Histogram Based CamShift

Author

Yang, Yang ; Wang, Zhiliang ; Sun, Dehui ; Zhang, Mengmeng ; Cheng, Nannan

Author_Institution

Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China

Volume

4

fYear

2010

fDate

4-6 June 2010

Firstpage

231

Lastpage

234

Abstract

The automatic objects tracking in videos plays important roles in computer vision applications. In this paper, we propose an automatic object tracking method hybrid with GMM and edge orientation histogram based CamShift. GMM is applied to detect objects motion. Different moving objects are separated by connected component analysis. And CamShift is processed by using edge orientation histogram to track objects. We demonstrate the effectiveness and efficiency of this approach by experimenting on several video sequences.

Keywords

computer vision; edge detection; image motion analysis; object detection; automatic object tracking; computer vision; edge orientation histogram; Application software; Cities and towns; Computer vision; Educational institutions; Histograms; Intelligent robots; Layout; Object detection; Robustness; Target tracking; CamShift; edge orientation histogram; gaussian mixture model; object tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Computing (ICIC), 2010 Third International Conference on

Conference_Location

Wuxi, Jiang Su

Print_ISBN

978-1-4244-7081-5

Electronic_ISBN

978-1-4244-7082-2

Type

conf

DOI

10.1109/ICIC.2010.329

Filename

5514061