# Lecture-10 - Alper Yilmaz Motivation Change Detection Skin...

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Alper Yilmaz UCF Computer Vision Lab. 1 Change Detection, Skin Detection Lecture-10 UCF Computer Vision Lab. 2 Motivation ! Detection of interesting objects in videos is the first step in the process of automated surveillance. • Focus of attention method greatly reduces the processing time required for tracking and activity recognition. UCF Computer Vision Lab. 3 Introduction ! Objectives: ! Given a sequence of images from a stationary camera identify pixels comprising ‘interesting’ objects. • General Solution –Model properties of the scene (e.g. color, texture e.t.c) at each pixel. – All independently moving objects are interesting! –Significant change in the properties indicates an interesting change. UCF Computer Vision Lab. 4 Introduction ! Problems in Realistic situations: ! Moving but uninteresting objects ! e.g. trees, flags or grass. – Long term illumination changes •e.g. time of day. – Quick illumination changes •e.g. cloudy weather – Shadows – Other Physical changes in the background •Dropping or picking up of objects – Initialization UCF Computer Vision Lab. 5 Segmenting Background UCF Computer Vision Lab. 6 Difference Pictures ! Jain, R. and Nagel, H. 1979. ``On the analysis of accumulative difference pictures from image sequences of real world scenes”. IEEE Trans. on Pattern Analysis and Machine Intelligence 1, 2, pp 206-214.

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Alper Yilmaz UCF Computer Vision Lab. 2 UCF Computer Vision Lab. 7 Background Subtraction - = ! Problem: Choosing a threshold ! Pixel is foreground if I 1 ( x , y )- 2 ( , ) ! ! otherwise background? ! What is the correct value of ! ? UCF Computer Vision Lab. 8 Setting a Threshold ! = 10 ! = 20 ! = 50 ! = 100 ! = 200 ! = 300 UCF Computer Vision Lab. 9 MODELING PIXEL INTENSITIES WITH A NORMAL DISTRIBUTION Each pixel intensity can be modeled by a Normal Distribution, defined in terms of a mean " and variance # 2 , as as N ( " , # 2 ). ). " and and # are called parameters. are called parameters. Useful when you wish to establish membership of a pixel to one of several models. N ( " , # 2 ) is a probability distribution ) is a probability distribution function defined by: ) 2 ( ) ( 2 2 2 2 2 1 ) , | ( # " \$# % % & x e f x UCF Computer Vision Lab. 10 Bi-variate Normal Distribution ! If we were interested in r-g , or g-b , or r- b ! The mean can be updated over time simply as UCF Computer Vision Lab. 11 Covariance ( ) * * + , & - 0 0 ( ) * * + , & - 2 1 0 0 ( ) * * + , & - 22 21 12 11 UCF Computer Vision Lab. 12 Tri-variate Normal
Alper Yilmaz UCF Computer Vision Lab. 3 UCF Computer Vision Lab. 13 Method I: P finder !

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## This note was uploaded on 10/04/2011 for the course CAP 6411 taught by Professor Shah during the Spring '09 term at University of Central Florida.

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Lecture-10 - Alper Yilmaz Motivation Change Detection Skin...

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