Name
Abstract | ||
|---|---|---|
Biometrie person recognition systems based on facial images are increasingly used in a wide range of applications. However, the potential for face spoofing attacks remains a significant challenge to the security of such systems and finding better means of detecting such presentation attacks has become a necessity. In this paper, we propose a new spoofing detection method, which is based on temporal changes in texture information. A novel temporal texture descriptor is proposed to characterise the pattern of change in a short video sequence named Temporal Co-occurrence Adjacent Local Binary Pattern (TCoALBP). Experimental results using the CASIA-FA, Replay Attack and MSU-MFSD datasets; the proposed method shows the effectiveness of the proposed technique on these challenging datasets. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ISBA.2018.8311464 | 2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis (ISBA) |
Keywords | Field | DocType |
texture information,spoofing detection method,face spoofing attacks,facial images,biometrie person recognition systems,temporal texture co-occurrence,facial biometrie presentation attack detection,Replay Attack,Temporal Co-occurrence Adjacent Local Binary Pattern,novel temporal texture descriptor | Histogram,Texture Descriptor,Pattern recognition,Spoofing attack,Computer science,Local binary patterns,Co-occurrence,Feature extraction,Artificial intelligence,Replay attack,Computational complexity theory | Conference |
ISBN | Citations | PageRank |
978-1-5386-2249-0 | 1 | 0.37 |
References | Authors | |
14 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pan Shi | 1 | 11 | 5.35 |
| Farzin Deravi | 2 | 296 | 36.61 |