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An Example of Course Project
Face Identification
Agenda
Why Face Identification?
• Useful
• Interesting
• Creating own dataset for extra credits
Data set
• The Extended Yale Face Database B
– 2414 images of 38 human
• Own data
– 100 images of 4 people
Classifiers
• SVM (Support Vector Machine)
– LIBSVM
– Self Implemented SVM Optimizer
• ANN (Artificial Neural Network)
• Coded in Matlab
Classifier Parameters
• SVM
– Kennel functions
• ANN
– Layers and units
Feature Selection
• Raw pixels
• Down-sampling pixels
• Extracted features
Compare Kernel Functions
100.00%
95.00%
90.00%
85.00%
80.00%
75.00%
70.00%
65.00%
60.00%
LIBSVM Multi-classifier
Improved one-vs-all
Compare Feature Numbers
105.00%
2500
100.00%
2000
95.00%
1500
90.00%
1000
85.00%
500
80.00%
10
100
1000
10000
Feature Number
0
100000
Accuracy
Time
ANN Learn Rate
Report
• 10 pages
Schedule
12 weeks total
3
2
2
3
Proposal
Prepare
dataset
2
Evaluation
& Report
Algorithms
implementation
Data
preprocessing
Lessons Learned
• Start early
• Review each other’s work
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