Title :
Building a Robust Appearance Model for Object Tracking
Author :
Yao, Zhijun ; Bin Feng ; Wang, Junwei ; Liu, Wenyu
Author_Institution :
Dept. of Electron. & Inf. Eng., HuaZhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
One of the challenges to creating robust trackers is the construction of robust appearance Model. This paper presents a robust appearance model for object tracking. The robust object distribution is acquired by comparing the two Gaussian Mixture Models of the object and background. The probability image generated by the robust object distribution is used for the CAMSHIFT tracking. Experiments on several video sequences show the effectiveness of the proposed method.
Keywords :
Gaussian processes; computer vision; object detection; probability; tracking; CAMSHIFT tracking; Gaussian mixture models; object tracking; probability image; robust appearance model; robust object distribution; Application software; Artificial intelligence; Buildings; Computational intelligence; Computer vision; Feature extraction; Histograms; Noise robustness; Probability; Target tracking; CAMSHIFT; Computer Vision; Feature Extraction; Gaussian Mixture Model; Object Tracking;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.165
