| Full text | |
| Author(s): |
Total Authors: 4
|
| Affiliation: | [1] Univ Fed Bahia, IVISION Lab, Salvador, BA - Brazil
[2] Sao Paulo State Univ, RECOGNA Lab, Sao Paulo - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE; v. 72, p. 368-381, JUN 2018. |
| Web of Science Citations: | 1 |
| Abstract | |
The growing use of control access systems based on face recognition shed light over the need for even more accurate systems to detect face spoofing attacks. In this paper, an extensive analysis on face spoofing detection works published in the last decade is presented. The analyzed works are categorized by their fundamental parts, i.e., descriptors and classifiers. This structured survey also brings a comparative performance analysis of the works considering the most important public data sets in the field. The methodology followed in this work is particularly relevant to observe temporal evolution of the field, trends in the existing approaches, to discuss still opened issues, and to propose new perspectives for the future of face spoofing detection. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 16/19403-6 - Energy-based learning models and their applications |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |