Local descriptors and similarity measures for frontal face recognition: A comparative analysis

1. Local descriptors and similarity measures for frontal face recognition: A comparative analysis 小组成员：周稻祥 报告人：周稻祥

2. About the Author: WitoldPedrycz • Research interests and activities: • Software Engineering • System modelling and knowledge discovery • Reconfigurable and evolvable architectures. • Pattern recognition • Personal Homepage：http://www.ece.ualberta.ca/~pedrycz/index.html • Department of Electrical and Computer Engineering, University of Alberta, Canada • Professor & Canada Research Chair & IEEE Fellow & Professional Engineer

3. About the Author: Marek Reformat • A member of the IEEE and ACM. • A member of program committees of several conferences related to computational intelligence and software engineering. • Actively involved in North American Fuzzy Information Processing Society (NAFIPS). • Research interests and activities: • Knowledge extraction and knowledge representation  • Semantic-based intelligent systems • Decision support • Software quality and maintenance • Personal Homepage： • http://www.ece.ualberta.ca/~reform/index.html

4. Similarity measures & Experimental results Contents Main process Local descriptors Gabor filter with LBP

5. Taxonomy Rotation invar Shifted LBP On pixel LBP,CS,RI Ternary LTP,DLTP Local descriptors On averaged ILBP,MBLBP,GRAB Distance based TPLBP,FPLBP Gabor phase quantization HGPP,LGPDP,LGXP MultiresolutionGabor,MB,GRAB local descriptors on Gabor filtered image Gabor magnitude LGBP,MHLVP,LGBPHS,MULGBP Selete subset U2,DLBP,SELBP Psychological WLD Three Dimen VLBP,LBP-TOP 3D GV-LBPTOP Gabor magnitude & phase ELGBP,MBP Derivative patterns ELGBP,LDP

6. Main process 1：选择合适的局部描述子，一般是选择基准点或者每一个像素点 2：局部描述子提升形成整体描述子，如果是基于每个像素得到的描述 子，通常是把每个区域的描述子进行连接。 3：通过某种相似度量，对未知图像的描述子与已知图像的描述子进行 匹配

7. Main process =[] V=[] H=[] Local pattern: pixel level description Histogram of Local patterns

8. Similarity measures & Experimental results Contents Main process Local descriptors Gabor filter with LBP

9. Baisc LBP etc Circular LBP Uniform-Ri LBP Basic LBP Local binary patterns: B Where A =2 Elongated LBP New Variants： Dominant LBP Statistically Effective LBP Hamming LBP Bilinear interpolation of a pixel 57

10. ILBP Local binary patterns: 100.11 Threshold - 1 Bins

11. ELBP Local binary patterns: L2 L1 L3 L4 Threshold Sign Magnitude

12. CLBP Original image Local binary patterns: Center gray level Local difference M S clbp_M clbp_C clbp_S clbp_map clbp_Histogram Magnitude Sign classifier

13. LTP Local binary patterns: 5 DLTP=| LTPU-LTPL|=135-40=95 (AELTP) LTP

14. Soft-LBP = Local binary patterns: =1- SLBP(

15. SILTP Gabor filter with LBP: [64(1-t)64(1+t)] t=0.1

16. MB-LBP Integral image Local binary patterns: D=4+1-(2+3)

17. GARB GRAB(General Region Assigned to binary) Local binary patterns: 某个阈值 如5 solving the orientation problem small variation in edge angles cause smaller variations in the binary representation #：noise & variations & rotation tolerant operator

18. CS-LBP Local binary patterns: CS-LB(pc)=-)*+-)* + -)* +-)*

19. TP-LBP Local binary patterns: TPLB)=) - ))* TPLB(p)= )-))*+ )-))*+ )-))*+ )-))*+ )-))*+ )-))*+ )-))*+ )-))*

20. FP-LBP Local binary patterns: FPLB)= ) - ))* FPLB(p)= )-))*+ )-))*+ )-))*+ )-))*

21. LDP Local binary patterns: 1：Robust against Gaussian white noise and non-monotonic illumination changes 2：Rotation invariant

22. VLBP Local binary patterns:

23. VLBP Local binary patterns:

24. LBP-TOP Local binary patterns:

25. LBP-TOP Local binary patterns:

26. LBP-TOP Local binary patterns:

27. LBP-TOP Local binary patterns:

28. Similarity measures & Experimental results Contents Main process Local descriptors Gabor filter with LBP

29. 连续 离散 Gabor filter with LBP

30. 连续 Gabor filter with LBP 离散 二维离散

31. 音调时间 振幅频率

32. 低频 高频 频 域 分 布 = + 空 间 分 布 = +

33. Gabor核函数： Dennis Gabor, 1946年提出窗口傅里叶变换进行时频分析，其中窗口函数就是高斯函数。 ( Gabor filter with LBP 其中：Z=(x,y) , / =5, =8,=; 卷积定理：

38. HGPP Gabor filter with LBP: 10 GGPP 80 GGPP 此时用的是实部与虚部而非幅值与相位值

39. HGPP Gabor filter with LBP: LGPP GGPP

40. LGPDP Gabor filter with LBP: 此时用的是相位值

41. LGXP = Gabor filter with LBP: ={0,1} ,,] 此时用的是相位值

42. Similarity measures & Experimental results Contents Main process Local descriptors Gabor filter with LBP

43. Similarity measures

44. Fusing sub-region 1: All sub-regional histograms concatenated 2: Sub-regions of two images are compared pair-wise and the results are aggregated

45. Fusing sub-region I1 I2 A:Feature level fusion LGBP_mag I1 I2 LGXP

46. Fusing sub-region I1 I1 Reduction dimensionality LGBP_mag 1: AdaBoost Others measure: 1:cosine distance measure 2:LDA I2 I2 LGXP 2: Borda count

50. Thank you