LITERATURE SURVEY OF AUTOMATIC FACE RECOGNITION ...

2.3.2 Processing Steps before Face Recognition………………..…..6
2.3.3 Analysis in Face Subspace………………………………….…...7
2.4 Technical Challenges…………………………………………………..7
2.5 Technical Solutions……………………………………………………..8
CHAPTER III. COMPLEXITY OF AFR
3.1 Some Major difficulty for AFR…………………………………….
…..10
CHAPTER IV. DIFFERENT TECHNIQUES FOR FACE RECOGNITION
4.1 Different Approach……………………………………………………13
4.1.1 Holistic Approach…………………………………………….13
4.1.2 Feature­based Approach…………………………………… 13
4.1.3 Hybrid Approach………………………………………………13
4.2 Eigenfaces Method………………………………….………………….14
4.3 Principal Component Analysis (PCA)…………………………………15
4.4 Independent Component Analysis (ICA)………………………..……16
4.5 Linear Discriminant Analysis (LDA)…………………………………..16
4.6 Evolutionary Pursuit (EP)………………………………………….…..17
4.7 Kernel Methods…………………………………………………….…..17
4.8 Trace Transform………………………………………………………..17
4.9 Support Vector Machine (SVM) …………………………………...…17
4.10 Elastic Bunch Graph Matching (EBGM) …………………..…….…17
4.11 Active Appearance Model (AAM) …………………………….…….18
4.12 3­D Morphable Model……………………………………………..….19
4.13 3­D Face Recognition……………………………………….……….19
4.14 Bayesian Framework………………………………………..………..20
4.15 Hidden Markov Models (HMM) ……………………………………..20
4.16 Boosting & Ensemble Solutions…………………………………….21
4.17 Nearest Feature Line Method…………………………………….…21
CHAPTER V. COMPARATIVE STUDY
5.1 Experimental Results……………………………………………..….…..23
5.2 Data Base…………………………………………………………………23
5.3 On the Four Individual Data Bases………………………….………….26
5.3.1 Eigenface……………………………………………………….26
5.3.2 The elastic matching…………………………………….…….27
5.3.3 Auto­Association and Classification Networks……….…….27
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