Download presentation

Presentation is loading. Please wait.

Published byDonavan Beadnell Modified about 1 year ago

1
Biometrics and Security Tutorial 3

2
1 (a) What is the scatter matrix (P4: 21)? Understand what about eigenvector and eigenvalue as well as their functions? (P4: 22)

3

4
Step 1

5

6
Step 2

7

8
Step 3

9

10
Step 4

11

12
Step 5

13

14

15
Step 6

16

17
1.(b) Understand the PCA application to facial recognition: Eigenface. (P4: 26-30)

18

19

20

21

22

23

24
1. (c) Compare two StatPR techniques, PCA and LDA (P4: 13) and point out their main difference (P4: 42-45) 1. (d) Linear discrimination analysis (LDA) is introduced in P5: Please understand the two steps in P5:37 and compare within-class scatter matrix with between-class scatter matrix.

25

26
Step 1

27
Step 2

28

29

30

31

32

33

34

35

36

37
2.There are three PR approaches: StatPR, SyatPR and NN. What difference between them (P4:4-10)? Based on your knowledge, can you give a simple application for each approach? 3.Please check the example of PR approaches in P4:10. Try to analysis the character “H” by statistical PR approach and structural PR approach. (StatPR approach - the feature set: (intersections, -, |, holes) and x=[2,1,4,0]; SyntPR approach - primitives and relations: ++++)

38

39

40
4.From P4:19-25, PCA method given by using image data is defined, which projects an image space with 644 dimension into 6 dimension eigenvector space. Please understand each step. 5.According to the figure in P4: 24, how to find its minimum λ if we hope to get rλ > 60? (λ = 3)

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google