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Sun, 08 Apr 2012 19:40:14 +0200

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Tue, 05 Apr 2011 21:23:12 +0200

corrected facerec_demo.cpp for OpenCV 2.4

There's a small bug in the facerec_demo.cpp, that ships with OpenCV 2.4. I'll put a corrected version upstream as soon as possible. However, here's a corrected version if you can't wait:

http://bytefish.de/dev/cpp/facerec_demo.cpp

2012/05/04 20:11 · Philipp Wagner · 0 Comments

opencv

opencv, visual studio and libfacerec

I've got a lot of mails from people, who have problems to use OpenCV with Microsoft Visual Studio 2008/2010. While I think it's unbelievably easy by using CMake, I am going to explain how to build the libfacerec demo without using CMake. I have illustrated each step with screenshots and detailed explanation, so it's easy for you to follow. I am going to use Microsoft Windows 7, Microsoft Visual Studio 2010 and OpenCV 2.3.1 in this tutorial.

Setting up OpenCV

First of all you'll need OpenCV. For this tutorial I suggest to download the OpenCV Superpack 2.3.1, which is available as OpenCV-2.3.1-win-superpack.exe at:

http://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.3.1/

There are a lot of other ways to install OpenCV, so please consult the http://opencv.willowgarage.com/wiki/ if you don't like the suggested one. The Superpack itself is not an installer, but a self-extracting archive. It contains the pre-built OpenCV library for VC9 (Microsoft Visual Studio 2008), VC10 (Microsoft Visual Studio 2010) and MinGW to mention a few. You'll only need the VC10 binaries for this tutorial.

Double-click the OpenCV-2.3.1-win-superpack.exe and select a folder to extract to. I'll choose D:\projects in this example:

The OpenCV superpack is no installer, so you'll need to manually add the OpenCV libraries to the DLL search path of Windows. The search paths of Windows are given in the PATH environment variable, which is a list of the directories to search, each separated by a semicolon.

Windows Vista and Windows 7 users

From the Desktop (or Start Menu), right-click My Computer and click Properties.
Click Advanced System Settings link in the left column.
In the System Properties window click the Environment Variables button.
In the Environment Variables window, highlight the Path variable in the Systems Variable section and click the Edit button. In the PATH variable each search path is separated with a semicolon.
At the end of the line add the following directories:
- D:\projects\opencv\build\x86\vc10\bin
- D:\projects\opencv\build\common\tbb\ia32\vc10

So you have to append a line like this to the existing PATH:

;D:\projects\opencv\build\x86\vc10\bin;D:\projects\opencv\build\common\tbb\ia32\vc10

Windows 2000 and Windows XP users

From the Desktop, right-click My Computer and click Properties.
In the System Properties window, click on the Advanced tab.
In the Advanced section, click the Environment Variables button.
In the Environment Variables window, highlight the Path variable in the Systems Variable section and click the Edit button. In the PATH variable each search path is separated with a semicolon.
At the end of the line add the following directories:
- D:\projects\opencv\build\x86\vc10\bin
- D:\projects\opencv\build\common\tbb\ia32\vc10

So you have to append a line like this to the existing PATH:

;D:\projects\opencv\build\x86\vc10\bin;D:\projects\opencv\build\common\tbb\ia32\vc10

Getting libfacerec

Next you'll need to download libfacerec, which is available from:

http://www.github.com/bytefish/libfacerec

If you don't know how to clone a github repository with git, then you can download the source from:

https://github.com/bytefish/libfacerec/downloads (zip, tar.gz)

Then extract the zip or tar.gz file to a folder of your choice, I am using D:\downloads\libfacerec in this tutorial. If you are using an other folder, then just keep it consistent.

Setting up Visual Studio

You'll now learn how to configure a Microsoft Visual Studio 10 C++ project with OpenCV. Parts might resemble the post by karlphilipp, which also explains how to configure OpenCV 2.3 on Visual Studio 2010. I won't reinvent the wheel, so you probably want to read hist post at:

http://stackoverflow.com/a/7014918/513875

The difference is, that I've decided to use pre-built Visual Studio 2010 (VC 10) libraries from the superpack. And I mention some pitfalls you'll encounter when compiling libfacerec.

Create an Empty project

Start Visual Studio and from the main menu select “File → New Project…“. Then create an “Empty Project”, name it libfacerec and store it in D:\projects:

Adding the libfacerec headers and sources

First of all the libfacerec headers and sources are added to our solution. For this copy the libfacerec header files from your extracted archive in D:\downloads\libfacerec\include to where your the solution is located in D:\projects\libfacerec\libfacerec. Also copy the source files from D:\downloads\libfacerec\src to D:\projects\libfacerec\libfacerec.

Now add the files to the Microsoft Visual Studio solution. In the Solution Explorer right click on Header Files and select Add → Existing Item…“, then select all *.hpp files you've just copied. Do the same for the source files and right click on Source Files and select all *.cpp files.

Your project now looks like this:

Additional Include Directories

Your project doesn't compile yet, because we didn't configure OpenCV. The first step is to set the additional include directories for our project. Go to the Project Properties by either right click on your project and select Properties or by pressing Alt + F7, in the new window do the following:

From the Configuration box (combo box in the top left), select All Configurations
Open Configuration Properties → C/C++ → General and edit the field Additional Include Directories to add these 3 include paths:
- D:\projects\opencv\build\include
- D:\projects\opencv\build\include\opencv
- D:\projects\opencv\build\include\opencv2

Additional Library Directories and Additional Dependencies

Then we need to add the libraries to build against. Again in the Project Properties Window do the following:

Add the path of the OpenCV libraries by Configuration Properties → Linker → General and on the Additional Library Directories field add:
- D:\projects\opencv\build\x86\vc10\lib

Then go to Configuration Properties → Linker → Input and in the Additional Dependencies field add:

opencv_highgui231.lib
opencv_core231.lib
opencv_imgproc231.lib

Build libfacerec

Finally libfacerec can be built. We are linking against the libraries:

opencv_core231.lib
opencv_highgui231.lib
opencv_imgproc231.lib

Those libraries have no Debug symbols, so we build libfacerec with the Release Configuration:

Then build the project and its executable by simply selecting Build → Build Solution (F7) from the Menu. And you should see:

Congratulations!

Running the Demo

Now to the Eigenfaces Demo. You need some data to make the examples work, sorry but I really can't include those face databases in my repository. First of all this. In the demo I have decided to read the images from a very simple CSV file. Why? Because it's the simplest platform-independent approach I can think of. However, if you know a simpler solution please ping me about it. Basically all the CSV file needs to contain are lines composed of a filename followed by a ; followed by the label (as integer number), making up a line like this:

/path/to/image.ext;0

Think of the label as the subject (the person) this image belongs to, so same subjects (persons) should have the same label. So let's make up an example. Download the AT&T Facedatabase from AT&T Facedatabase and the corresponding CSV file from at.txt, which looks like this (file is without … of course):

./at/s1/1.pgm;0
./at/s1/2.pgm;0
...
./at/s2/1.pgm;1
./at/s2/2.pgm;1
...
./at/s40/1.pgm;39
./at/s40/2.pgm;39

Imagine I have extracted the files to D:/data/at and have downloaded the CSV file to D:/data/at.txt.

Then I would simply Search & Replace ./ with D:/data/. You can do that in an editor of your choice, every sufficiently advanced editor can do this. Once you have a CSV file with valid filenames and labels, you can run the demo by with the path to the CSV file as parameter:

D:\projects\libfacerec\Release\libfacerec.exe D:/data/at.txt

and you should see (Note I have switched to the Eigenfaces model in the demo. Latest version in trunk is Fisherfaces!):

So yes. I am pretty sure all this also works in Microsoft Windows.

2012/04/19 01:13 · Philipp Wagner · 0 Comments

opencv

opencv developer

I am now in the developers list of OpenCV: http://code.opencv.org/projects/opencv. I'll help maintaining and enhancing the contributed face recognition algorithms and I'll work on the documentation. If you have any suggestions what's missing in there, please let me know.

2012/04/16 07:23 · Philipp Wagner · 0 Comments

opencv

aligning face images

Some people have asked me how I've aligned the face images in my articles. Giving people my ImageMagick hack is embarrassing for me, so I've decided to rewrite it into a Python script. You don't need to copy and paste it, as the script comes with the source folder of my Guide on Face Recognition: src/py/crop_face.py.

The code is really easy to use. To scale, rotate and crop the face image you just need to call CropFace(image, eye_left, eye_right, offset_pct, dest_sz), where:

eye_left is the position of the left eye
eye_right is the position of the right eye
offset_pct is the percent of the image you want to keep next to the eyes (horizontal, vertical direction)
dest_sz is the size of the output image

If you are using the same offset_pct and dest_sz for your images, they are all aligned at the eyes.

example

Imagine we are given this photo of Arnold Schwarzenegger, which is under a Public Domain license.

The (x,y)-position of the eyes is approximately (252,364) for the left and (420,366) for the right eye. Now you only need to define the horizontal offset, vertical offset and the size your scaled, rotated & cropped face should have. Here are some examples:

Configuration	Cropped, Scaled, Rotated Face
0.1 (10%), 0.1 (10%), (200,200)
0.2 (20%), 0.2 (20%), (200,200)
0.3 (30%), 0.3 (30%), (200,200)
0.2 (20%), 0.2 (20%), (70,70)

crop_face.py

#!/usr/bin/env python
# Software License Agreement (BSD License)
#
# Copyright (c) 2012, Philipp Wagner
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
#  * Redistributions of source code must retain the above copyright
#    notice, this list of conditions and the following disclaimer.
#  * Redistributions in binary form must reproduce the above
#    copyright notice, this list of conditions and the following
#    disclaimer in the documentation and/or other materials provided
#    with the distribution.
#  * Neither the name of the author(s) nor the names of its
#    contributors may be used to endorse or promote products derived
#    from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
 
import sys, math, Image
 
def Distance(p1,p2):
  dx = p2[0] - p1[0]
  dy = p2[1] - p1[1]
  return math.sqrt(dx*dx+dy*dy)
 
def ScaleRotateTranslate(image, angle, center = None, new_center = None, scale = None, resample=Image.BICUBIC):
  if (scale is None) and (center is None):
    return image.rotate(angle=angle, resample=resample)
  nx,ny = x,y = center
  sx=sy=1.0
  if new_center:
    (nx,ny) = new_center
  if scale:
    (sx,sy) = (scale, scale)
  cosine = math.cos(angle)
  sine = math.sin(angle)
  a = cosine/sx
  b = sine/sx
  c = x-nx*a-ny*b
  d = -sine/sy
  e = cosine/sy
  f = y-nx*d-ny*e
  return image.transform(image.size, Image.AFFINE, (a,b,c,d,e,f), resample=resample)
 
def CropFace(image, eye_left=(0,0), eye_right=(0,0), offset_pct=(0.2,0.2), dest_sz = (70,70)):
  # calculate offsets in original image
  offset_h = math.floor(float(offset_pct[0])*dest_sz[0])
  offset_v = math.floor(float(offset_pct[1])*dest_sz[1])
  # get the direction
  eye_direction = (eye_right[0] - eye_left[0], eye_right[1] - eye_left[1])
  # calc rotation angle in radians
  rotation = -math.atan2(float(eye_direction[1]),float(eye_direction[0]))
  # distance between them
  dist = Distance(eye_left, eye_right)
  # calculate the reference eye-width
  reference = dest_sz[0] - 2.0*offset_h
  # scale factor
  scale = float(dist)/float(reference)
  # rotate original around the left eye
  image = ScaleRotateTranslate(image, center=eye_left, angle=rotation)
  # crop the rotated image
  crop_xy = (eye_left[0] - scale*offset_h, eye_left[1] - scale*offset_v)
  crop_size = (dest_sz[0]*scale, dest_sz[1]*scale)
  image = image.crop((int(crop_xy[0]), int(crop_xy[1]), int(crop_xy[0]+crop_size[0]), int(crop_xy[1]+crop_size[1])))
  # resize it
  image = image.resize(dest_sz, Image.ANTIALIAS)
  return image
 
if __name__ == "__main__":
  image =  Image.open("arnie.jpg")
  CropFace(image, eye_left=(252,364), eye_right=(420,366), offset_pct=(0.1,0.1), dest_sz=(200,200)).save("arnie_10_10_200_200.jpg")
  CropFace(image, eye_left=(252,364), eye_right=(420,366), offset_pct=(0.2,0.2), dest_sz=(200,200)).save("arnie_20_20_200_200.jpg")
  CropFace(image, eye_left=(252,364), eye_right=(420,366), offset_pct=(0.3,0.3), dest_sz=(200,200)).save("arnie_30_30_200_200.jpg")
  CropFace(image, eye_left=(252,364), eye_right=(420,366), offset_pct=(0.2,0.2)).save("arnie_20_20_70_70.jpg")

2012/04/10 21:58 · Philipp Wagner · 0 Comments

python

face recognition in iOS 5

Pedro Centieiro notified me about his Apple iOS 5 face recognition project, called midian. The project uses OpenCV (>2.0) and comes with an extensive README, which explains how to build the code:

http://github.com/pcentieiro/midian

It includes parts of libfacerec, with tweaks to make it work for Apple iOS 5. Thanks for this!

The project is a great start for anyone who wants to create an Apple iOS 5 project with OpenCV.

2012/03/29 09:25 · Philipp Wagner · 0 Comments

ios, opencv

libfacerec now merged into opencv

libfacerec has now been merged into the contrib module of OpenCV:

http://code.opencv.org/projects/opencv/repository/revisions/7619

Thanks a lot to Vadim Pisarevsky for helping with it.

2012/03/25 11:28 · Philipp Wagner · 0 Comments

libfacerec, opencv, cpp

libfacerec update

I have just released version 0.02 of libfacerec, which is now available at http://www.github.com/bytefish/libfacerec. libfacerec is a modern face recognition library for the OpenCV C++ API and comes with:

Eigenfaces as described in: Turk, M., and Pentland, A. “Eigenfaces for recognition.”. Journal of Cognitive Neuroscience 3 (1991), 71–86.
Fisherfaces as described in: Belhumeur, P. N., Hespanha, J., and Kriegman, D. “Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection.”. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 7 (1997), 711–720.
Local Binary Patterns Histograms as described in: Ahonen, T., Hadid, A., and Pietikainen, M. “Face Recognition with Local Binary Patterns.”. Computer Vision - ECCV 2004 (2004), 469–481.

The library was written for OpenCV 2.3.1 with the upcoming OpenCV 2.4 in mind, so I don't support OpenCV versions earlier than 2.3.1. This project comes as a CMake project with a well-documented API and complete examples for:

Face Recognition with Eigenfaces, Fisherfaces, Local Binary Patterns Histograms
Gender Classification (with Fisherfaces)
- http://bytefish.de/dev/libfacerec/api/example/example_gender_classification.html
ColorMaps in OpenCV
- http://bytefish.de/dev/libfacerec/api/example/example_colormap.html

If you are interested in reading the whole documentation, I've uploaded the HTML version to http://www.bytefish.de/dev/libfacerec/.

2012/03/22 18:28 · Philipp Wagner · 0 Comments

libfacerec, opencv, cpp

introducing libfacerec

I've started working on a face recognition library for the OpenCV C++ API: libfacerec.

The library is header-only and has no additional dependencies, so using it is as simple as adding it to your include path. The Eigenfaces and Fisherfaces methods have already been implemented and most parts of the library have been tested (finally!). A LBP-based face recognition is planned & almost completed, I just have to finish writing the tests for it.

Please consider the library as Work In Progress, there are probably some interface changes coming.

2012/03/13 00:32 · Philipp Wagner · 0 Comments

opencv, cpp

page update

Sorry for the downtime this afternoon. I've updated to a recent DokuWiki version, because the old one was ancient. Please contact me if you find any errors or dead links.

2012/03/02 16:26 · Philipp Wagner · 0 Comments

update

face recognition with opencv2

I've recently pushed some code to perform face recognition with OpenCV2 into my github repository. If you've ever researched on face recognition I am pretty sure you've noticed: there's a gigantic number of publications, but source code is kept like a secret. Since I've got some positive feedback on Machine Learning with OpenCV2, I thought I write a document on:

It's the kind of guide I've wished for, when I was working myself into face recognition. It helps you with installing OpenCV2 on your machine and explains you how to build a project on Windows and Linux. The Eigenfaces and Fisherfaces method are explained in detail, prototyped with Python, GNU Octave/MATLAB and implemented with OpenCV2's C++ API. A basic knowledge of C++ is assumed and administrative rights for your machine are a plus. I've decided to use MinGW (the GCC port for Windows) as C/C++ compiler for Windows, because it works great with OpenCV2 and comes under terms of a public license (please see mingw.org/license for details). If someone checks the install guide for Visual Studio 2008/2010, I would be happy to add it to the document. I guess you only have to generate a Visual Studio project with CMake, open and compile it; but I don't have Visual Studio right now to check it.

The code and document is released under a BSD license, so feel free to use it for your commercial and academic projects. Note: the latest version of the document and code can be obtained from the projects github repository:

http://www.github.com/bytefish/facerecognition_guide

2012/01/31 23:03 · Philipp Wagner · 5 Comments

opencv, octave, cpp

Older entries >>

documents

Wed, 21 Mar 2012 09:59:28 +0200

… will be translated one day.

Here are some documents we wrote. Some of them are in german, but they'll get translated as soon as possible. Non-german readers are highly encouraged to look at all the beautiful pictures inside! If you have a question, just mail one of us.

Title	Author(s)	Document	Notes
Face Recognition with OpenCV2	Philipp Wagner	PDF (GNU Octave/MATLAB version, English)	The kind of guide I've wished for, when I was working myself into face recognition. Helps you with installing OpenCV2 and building projects on Windows and Linux. The Eigenfaces and Fisherfaces method are explained and implemented with Python, GNU Octave/MATLAB and OpenCV2's C++ API. Sourcecode and latest revision available at github.com/bytefish/facerecognition_guide.
Face Recognition with OpenCV2	Philipp Wagner	PDF (Python version, English)
Statistical Machine Learning with OpenCV	Philipp Wagner (but thanks to Filip for his amazing inkscape skills!)	PDF (English)	Is an introduction into statistical machine learning with OpenCV. It contains a guide for setting up OpenCV on Windows and Linux. A brief introduction and code for Support Vector Machines and Multilayer Perceptrons is given. Good to get started with OpenCV and its Machine Learning library!
Einfuehrung in MapReduce	Filip Martinovský, Philipp Wagner, Stefan Heinze	PDF (German)	Is an introduction to MapReduce and gives some ideas on how to implement it in Erlang.
Distributed Hash Tables	Filip Martinovský, Philipp Wagner	PDF (German)	Reads like a tutorial on how to implement distributed hash tables. Chord, a protocol for distributed hash tables, is described and implemented in Erlang.
Gesichtserkennung mit Eigenfaces	Filip Martinovský, Philipp Wagner	PDF (German)	Explains face recognition with Eigenfaces. Shows the performance of a prototype on two datasets (Yale Facedatabase A, AT&T Dataset).
XML Processing in Scheme	Filip Martinovský, Philipp Wagner	PDF (English)	Explains Xml processing in Scheme: SXML. Rather old.
XML Verarbeitung in Scheme	Filip Martinovský, Philipp Wagner	PDF (German)	Explains Xml processing in Scheme: SXML. Rather old.

erlang, distributed hashtable, mapreduce, eigenfaces, xml, scheme, opencv, cpp

home

Thu, 10 Feb 2011 09:40:18 +0200

Welcome to my page. It contains things I work on, a wiki, a blog and documents I wrote. There are articles on Erlang, OpenCV and a lot of other things I had fun with.

Enjoy your stay.

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Mon, 27 Dec 2010 17:25:27 +0200

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