Title :
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
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;
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
DOI :
10.1109/ICIC.2010.329
