Liveness detection based on 3d FACE SHAPE ... - University of Malta

IWBF 2014 2nd International Workshop on Biometrics and Forensics 27‐28th March, Valletta, Malta

TOWARDS PRACTICAL SPACE‐VARIANT BASED  FACE RECOGNITION AND AUTHENTICATION Enrico Grosso, Andrea Lagorio, Luca Pulina, and Massimo Tistarelli Computer Vision Laboratory - University of Sassari, ITALY

CONTEXT AND MOTIVATION Combining the extraction of salient points and space‐variant descriptors, a novel and efficient method for face recognition and authentication can be implemented. This method is called BSV. Experimental results demonstrate that this approach is computationally feasible and guarantees a significant increase in accuracy with respect to the original SIFT approach.

THE BOOSTED SPACE VARIANT FRAMEWORK

BSV(img1, img2) 1 kp1  = SIFTDETECT(img1) 2 kp2  = SIFTDETECT(img2) 3 desc1 =  SIFTEXTRACT(kp1) 4 desc2  = SIFTEXTRACT(kp2) 5 skp1 = NIL 6 skp2 = NIL 7 SIFTMATCHER(desc1, desc2, skp1, skp2) 8 score = ‐1 9 for i = 0 to SIZE(skp1) 10 currScore = LPCORR(skp1[i], skp2[i]) 11 if currScore > score then 12 score = currScore 13 return score

Example of a single space variant filter  centered on a generic point

RESULTS FACE RECOGNITION (FERET DATABASE) Accuracy

BSV

GSIFT

SIFT

82%

78%

72%

FACE AUTHENTICATION (BANCA DATABASE) MC

UD

UA

P

MC

UD

UA

P

BSV

7.12%

23.22% 19.43%

23.31%

BSV

3.73%

24.64% 19.00%

21.45%

GSIFT

7.02%

12.43% 18.32%

18.09%

GSIFT

2.00%

12.82% 17.18%

15.55%

SIFT

12.12%

39.44% 28.37%

33.72%

SIFT

7.82%

42.18% 29.55%

38.91%

WER (1)

WER (0.1) MC

UD

UA

P

BSV

10.27%

21.36% 19.00%

25.54%

GSIFT

11.00%

10.36% 18.82%

20.45%

SIFT

15.18%

34.82% 34.45%

29.09%

WER (10)