Biometric Antispoofing Methods: A Survey in Face Recognition <s> B. FACE ANTI-SPOOFING <s> Automatic face recognition systems have made great strides. They still, however cannot cope with changes due to lighting and cannot detect disguises, Both of these issues are critical for the employment of face recognition systems in high security applications, such as embassy perimeters, federal plazas, mid the like. We propose novel imaging solutions that address these difficult problems. We demonstrate with theoretical and experimental arguments that a dual-band fusion system in the near infrared can segment human faces much more accurately than traditional visible band face detection systems. Face detection is useful by itself as an early warning method in certain surveillance applications. Accurate face delineation can also improve the performance of face recognition systems in certain difficult scenarios, particularly in outside environments. We also demonstrate with theoretical and experimental arguments that the upper band of the near infrared (1.4-2.4 /spl mu/m) is particularly advantageous for disguise detection purposes. This is attributable to the unique and universal properties of the human skin in this sub-band. We conclude the paper with a description of our ongoing and future efforts. <s> BIB001 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> B. FACE ANTI-SPOOFING <s> Spoofing with photograph or video is one of the most common manner to circumvent a face recognition system. In this paper, we present a real-time and non-intrusive method to address this based on individual images from a generic webcamera. The task is formulated as a binary classification problem, in which, however, the distribution of positive and negative are largely overlapping in the input space, and a suitable representation space is hence of importance. Using the Lambertian model, we propose two strategies to extract the essential information about different surface properties of a live human face or a photograph, in terms of latent samples. Based on these, we develop two new extensions to the sparse logistic regression model which allow quick and accurate spoof detection. Primary experiments on a large photo imposter database show that the proposed method gives preferable detection performance compared to others. <s> BIB002 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> B. FACE ANTI-SPOOFING <s> Spoofing identities using photographs is one of the most common techniques to attack 2-D face recognition systems. There seems to exist no comparative studies of different techniques using the same protocols and data. The motivation behind this competition is to compare the performance of different state-of-the-art algorithms on the same database using a unique evaluation method. Six different teams from universities around the world have participated in the contest. Use of one or multiple techniques from motion, texture analysis and liveness detection appears to be the common trend in this competition. Most of the algorithms are able to clearly separate spoof attempts from real accesses. The results suggest the investigation of more complex attacks. <s> BIB003 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> B. FACE ANTI-SPOOFING <s> Spoofing attacks are one of the security traits that biometric recognition systems are proven to be vulnerable to. When spoofed, a biometric recognition system is bypassed by presenting a copy of the biometric evidence of a valid user. Among all biometric modalities, spoofing a face recognition system is particularly easy to perform: all that is needed is a simple photograph of the user. In this paper, we address the problem of detecting face spoofing attacks. In particular, we inspect the potential of texture features based on Local Binary Patterns (LBP) and their variations on three types of attacks: printed photographs, and photos and videos displayed on electronic screens of different sizes. For this purpose, we introduce REPLAY-ATTACK, a novel publicly available face spoofing database which contains all the mentioned types of attacks. We conclude that LBP, with ∼15% Half Total Error Rate, show moderate discriminability when confronted with a wide set of attack types. <s> BIB004 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> B. FACE ANTI-SPOOFING <s> Face antispoofing has now attracted intensive attention, aiming to assure the reliability of face biometrics. We notice that currently most of face antispoofing databases focus on data with little variations, which may limit the generalization performance of trained models since potential attacks in real world are probably more complex. In this paper we release a face antispoofing database which covers a diverse range of potential attack variations. Specifically, the database contains 50 genuine subjects, and fake faces are made from the high quality records of the genuine faces. Three imaging qualities are considered, namely the low quality, normal quality and high quality. Three fake face attacks are implemented, which include warped photo attack, cut photo attack and video attack. Therefore each subject contains 12 videos (3 genuine and 9 fake), and the final database contains 600 video clips. Test protocol is provided, which consists of 7 scenarios for a thorough evaluation from all possible aspects. A baseline algorithm is also given for comparison, which explores the high frequency information in the facial region to determine the liveness. We hope such a database can serve as an evaluation platform for future researches in the literature. <s> BIB005 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> B. FACE ANTI-SPOOFING <s> The problem of detecting face spoofing attacks (presentation attacks) has recently gained a well-deserved popularity. Mainly focusing on 2D attacks forged by displaying printed photos or replaying recorded videos on mobile devices, a significant portion of these studies ground their arguments on the flatness of the spoofing material in front of the sensor. In this paper, we inspect the spoofing potential of subject-specific 3D facial masks for 2D face recognition. Additionally, we analyze Local Binary Patterns based coun-termeasures using both color and depth data, obtained by Kinect. For this purpose, we introduce the 3D Mask Attack Database (3DMAD), the first publicly available 3D spoofing database, recorded with a low-cost depth camera. Extensive experiments on 3DMAD show that easily attainable facial masks can pose a serious threat to 2D face recognition systems and LBP is a powerful weapon to eliminate it. <s> BIB006 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> B. FACE ANTI-SPOOFING <s> As a crucial security problem, anti-spoofing in biometrics, and particularly for the face modality, has achieved great progress in the recent years. Still, new threats arrive inform of better, more realistic and more sophisticated spoofing attacks. The objective of the 2nd Competition on Counter Measures to 2D Face Spoofing Attacks is to challenge researchers to create counter measures effectively detecting a variety of attacks. The submitted propositions are evaluated on the Replay-Attack database and the achieved results are presented in this paper. <s> BIB007
Although the first face anti-spoofing works date back more than a decade BIB001 , it has not been until the last three years that this technology has experimented a real revolution under the umbrella of the TABULA RASA European project focused on the study of spoofing attacks to biometric systems  . Another decisive factor for the development of new protection methods against direct attacks has been the acquisition and distribution of several public face spoofing databases, that have made possible for researchers to focus on the design of efficient countermeasures and not on data acquisition issues BIB002 , BIB004 , BIB005 , BIB006 . Both factors have fostered the recent publication of multiple techniques in 2D face anti-spoofing and to initiate a promising research line in new protection algorithms for 3D face recognition systems against mask attacks. In the next sections we review the works that have addressed so far the challenging problem of face antispoofing. To this end, we follow the general categorization presented in Sect. II and depicted in Fig. 3 . As overall reference, the advantages and drawbacks of each general group of techniques are summarized in Table 3 . However, to understand the specific potential uses of every particular algorithm readers are referred to corresponding works. As may be seen in Table 3 , it is difficult to clearly select one technique over the others, as their performance is highly dependent on the attacks and the use case considered. It is commonly observed that anti-spoofing methods fail to perform consistently across databases, experimenting a significant loss of accuracy when they are tested under different conditions to those for which they were designed. As such, usually the best results are achieved through the combination of several complementary algorithms or features, so that the weaknesses of some are covered by the strengths of others and viceversa BIB007 , BIB003 .