src
所属分类：图形图像处理
开发工具：matlab
文件大小：761KB
下载次数：175
上传日期：2012-09-20 16:47:35
上 传 者：
pwei007
说明： 背景减除的完整算法，《A Statistical Approach for Real-time Robust Background Subtraction and Shadow Detection》作者源代码
(The "src" folder contains all of the source code.
To run the program, follow these simple steps:
1. Start MATLAB and ensure the "src" folder is your current working
directory.
2. Edit "bs.m" and "classify.m" so that the file paths point to the
proper directories as specified.
3. In the MATLAB environment type "bs" which will train the background
model from the sequence you specified in (2).
4. In the MATLAB environment type "classify" which will classify the
sequence of images you specified in (2).
5. Now the classified images should be saved to disk in the folder you
specified in (2).)
文件列表:
src\backgroundModel.m (1569, 2005-12-02)
src\brightnessDistortion.m (1098, 2005-12-02)
src\bs.m (1640, 2005-12-02)
src\classify.m (721, 2005-12-02)
src\classifyImage.m (1544, 2005-12-02)
src\colorDistortion.m (762, 2005-12-02)
src\data (0, 2005-12-02)
src\data\images (0, 2005-12-02)
src\data\images\mov1 (0, 2005-12-02)
src\data\images\mov1\Frame250.jpg (8604, 2005-11-29)
src\data\images\mov1\Frame251.jpg (8603, 2005-11-29)
src\data\images\mov1\Frame252.jpg (8603, 2005-11-29)
src\data\images\mov1\Frame253.jpg (8630, 2005-11-29)
src\data\images\mov1\Frame254.jpg (8566, 2005-11-29)
src\data\images\mov1\Frame255.jpg (8566, 2005-11-29)
src\data\images\mov1\Frame256.jpg (8551, 2005-11-29)
src\data\images\mov1\Frame257.jpg (8554, 2005-11-29)
src\data\images\mov1\Frame258.jpg (8554, 2005-11-29)
src\data\images\mov1\Frame259.jpg (8558, 2005-11-29)
src\data\images\mov1\Frame260.jpg (8584, 2005-11-29)
src\data\images\mov1\Frame261.jpg (8584, 2005-11-29)
src\data\images\mov1\Frame262.jpg (8582, 2005-11-29)
src\data\images\mov1\Frame263.jpg (8554, 2005-11-29)
src\data\images\mov1\Frame264.jpg (8554, 2005-11-29)
src\data\images\mov1\Frame265.jpg (8634, 2005-11-29)
src\data\images\mov1\Frame266.jpg (8606, 2005-11-29)
src\data\images\mov1\Frame267.jpg (8606, 2005-11-29)
src\data\images\mov1\Frame268.jpg (8592, 2005-11-29)
src\data\images\mov1\Frame269.jpg (8634, 2005-11-29)
src\data\images\mov1\Frame270.jpg (8634, 2005-11-29)
src\data\images\mov1\Frame271.jpg (8614, 2005-11-29)
src\data\images\mov1\Frame272.jpg (8578, 2005-11-29)
src\data\images\mov1\Frame273.jpg (8578, 2005-11-29)
src\data\images\mov1\Frame274.jpg (8637, 2005-11-29)
src\data\images\mov1\Frame275.jpg (8627, 2005-11-29)
src\data\images\mov1\Frame276.jpg (8627, 2005-11-29)
src\data\images\mov1\Frame277.jpg (8619, 2005-11-29)
src\data\images\mov1\Frame278.jpg (8632, 2005-11-29)
src\data\images\mov1\Frame279.jpg (8632, 2005-11-29)
src\data\images\mov1\Frame280.jpg (8515, 2005-11-29)
... ...
==================================================
CS 4495 Final Project
Robust Background Subtraction and Shadow Detection
12/2/2005
Mark DeJesus - gtg338q
==================================================
-----------------
ABOUT THE PROGRAM
-----------------
This project is based on the paper “A Statistical Approach for Real-Time
Robust Background Subtraction and Shadow Detection” by Thanarat Horprasert,
David Harwood, and Larry S. Davis at the University of Maryland.
This paper presents a novel algorithm for detecting moving objects from a
static background scene that contains shading and shadows using color
images. We develop a robust and efficiently computed background subtraction
algorithm that is able to cope with local illumination changes, such as
shadows and highlights, as well as global illumination changes. The
algorithm is based on a proposed computational color model, which separates
the brightness from the chromaticity component.
The program was coded in MATLAB and consists of seven separate source code
files to complete the program:
bs.m – Function called to model the background. Contains parameters such
as what images to use for the background model and the size of the images.
readSequence.m – Reads in the sequence of images to be used for the
background model from disk.
backgroundModel.m – Calculates the background model.
brightnessDistortion.m – Calculates the brightness distortion
for a pixel.
colorDistortion.m – Calculates the color distortion for a pixel.
classify.m – Function called to classify the pixels of a sequence
of images and saves the result to disk.
classifyImage.m – Classifies the pixels of a single image.
-------------------
RUNNING THE PROGRAM
-------------------
The "src" folder contains all of the source code.
To run the program, follow these simple steps:
1. Start MATLAB and ensure the "src" folder is your current working
directory.
2. Edit "bs.m" and "classify.m" so that the file paths point to the
proper directories as specified.
3. In the MATLAB environment type "bs" which will train the background
model from the sequence you specified in (2).
4. In the MATLAB environment type "classify" which will classify the
sequence of images you specified in (2).
5. Now the classified images should be saved to disk in the folder you
specified in (2).
=========================================================================
See http://swiki.cc.gatech.edu:8080/cs4495-fl04/309 for more information.
=========================================================================
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