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# Independent Component Analysis-Based Background Subtraction for Indoor Surveillance - PowerPoint PPT Presentation

Independent Component Analysis-Based Background Subtraction for Indoor Surveillance. INTRODUCTION.

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## PowerPoint Slideshow about ' Independent Component Analysis-Based Background Subtraction for Indoor Surveillance' - abdul-gordon

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### Independent Component Analysis-Based BackgroundSubtraction for Indoor Surveillance

• propose a simple and fast background subtraction scheme without background model updating, and yet it is tolerable to changes in room lighting for indoor surveillance using Independent Component Analysis (ICA).

A. Basic ICA Model

• The observed mixture signals X can be expressed as

X = AS where A is an unknown mixing matrix, and S represents the latent source signals.

• The ICA model describes how the observed mixture signals X are generated by a process that uses the mixing matrix A to mix the latent source signals S.

A. Basic ICA Model

• The source signals are assumed to be mutually statistically independent. Based on the assumption, the ICA solution is obtained in an unsupervised learning process that finds a de-mixing matrix W. The matrix W is used to transform the observed mixture signals X to yield the independent signals, i.e., WX = Y. The independent signals Y are used as the estimates of the latent source signals S. The components of Y, called independent components, are required to be as mutually independent as possible.

B. Proposed ICA Model

• In order to separate foreground objects from the background in a scene image, we need at least two sample images to construct the mixture signals in the ICA model.

• Let the sample images be of size m X n. Each sample image is organized as a row vector of K dimensions, where K = m ∙ n. Denote by Xb = [xb1 , xb2 , ∙ ∙ ∙ , xbK]the reference background image containing no foreground objects, and Xf = [xf1 , xf2 , ∙ ∙ ∙ , xfK]the foreground image containing an arbitrary foreground object in the stationary background.

B. Proposed ICA Model

• In the training stage of the proposed background subtraction scheme, the ICA model is given by

Y = W∙XT

• Single Reference Background

• Single Reference Background

• Multiple Reference Background

• Multiple Reference Background

• Effect of Varying Foreground Objects