Moving Object Tracking using Gaussian Mixture Model and Optical Flow

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Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
In this paper, the authors propose a new tracking method that uses Gaussian Mixture Model (GMM) and Optical Flow approach for object tracking. The GMM approach consists of three different Gaussian distributions, the average, standard deviation and weight respectively. There are two important steps to establish the background for model, and background updates which separate the foreground and background. This paper combines the GMM and Optical Flow object tracking. The advantages of Optical Flow are quick calculations and the disadvantage is a lack of complete object tracking.
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