Label the group photo locate and identify faces and label them
Mar 28, 2015
Label the group photo
locate and identify faces and label them
Ramona CiulpanWebmaster
Label the group photo
locate and identify faces and label them
Kornel Toth SVM, Database
Label the group photo
locate and identify faces and label them
Mircea FocşaPPT Presentation
Label the group photo
locate and identify faces and label them
Krisztian Olle Project manager
Label the group photo
locate and identify faces and label them
Project Description
Label the group photo- locate and identify faces and label them
• Input group photo ( for example 10 people)• Segment it to isolate people/faces• Number the faces• Extract the faces• Build of library of faces• From photos of similar faces try to find that person on
the group photo
Face DetectionFinding faces is complicated?
Possible solution
Neural Network Template matching Principal Component Analysis Support Vector Machine
Possible solution
Neural Network Template matching Principal Component Analysis Support Vector Machine
Support Vector Machines algorithm
Minimize W(Λ)=- ΛT 1 + 1/2 Λ T D Λ ΛSubject to
ΛT y = 0Λ-C1 ≤ 0- Λ ≤ 0
Face detection (I)• Create an images database
– 266 pictures: 150 faces + 116 non-faces
. . .
• Preprocessing– Gray scale transformation– Histogram equalization– Adjust resolution to 30x40 pixel
• Training the SVM based on that 266 vectors, using a polynomial kernel.
Face detection (II)
• Moving over the input image with a 30x40 pixel sub window
• Histogram equalization of a sub window• Classification by SVM• Removing intersections
Face recognition
• Training the SVM based on the people faces who want to recognize
• Classifying the detected faces• Labeling the known faces
Implementation (I)
Input group photo
Isolate people / faces
Number the faces
Implementation (II)
Input group photo
Isolate people / faces
Number the faces
Implementation (III)
Extract the faces
Implementation (IV)
Build of library of faces
Implementation (V)
Label the faces
Train the SVM with new set of vectors
Results
Image name Resolution# of
faces# of tests
# of found faces
Time (sec.)
False
Classific.
csoport.pgm 600x398 15 9600 13 11.45 6
team2.pgm 700x465 4 13020 4 15.077 0
team3.pgm 600x398 4 9600 4 14.671 0
team31.pgm 500x331 4 6700 4 10.499 0
team4.pgm 500x331 4 6700 4 10.515 0
team41.pgm 400x265 4 4240 4 5.984 0
test5.pgm 500x332 5 6700 4 9.937 1
Examples
Future Plans
• Multi-resolution image pyramid• Better face databases• Better face recognition databases• Improve the speed • Improve the masking technique
Thank You!How many faces ?
11
33
22
44 55 66
77
8899
1111
1010
References
• Open Source Computer Vision Library Reference Manual http://developer.intel.com/
• Guodong Guo, Stan Z. Li, and Kapluk Chan: “Face Recognition by Support Vector Machines” Proceeding of Fourth IEEE International Conference on Automatic Face and Gesture Recognition, 2000 Grenoble, France.
• Edgar Osuna, Robert Freund: “Training Support Vector Machines: an Application to Face Detection”. Proceeding of CVPR’97, 1997 Puerto Rico
• The Face Detection Homepage http://home.t-online.de/home/Robert.Frischholtz/face.htm