International Standardization on Face Recognition Technology

Transcription

1 International Standardization on Face Recognition Technology Wonjun Hwang 1, Seok Cheol Kee 1 1 Computing Lab., Samsung Advanced Institute of Technology Mt. 14-1, Noengseo-Ri, Giheung-Eup, Yonging-Si, Gyeonggi-Do, Korea , {wj.hwang, sckee}@samsung.com Abstract. This paper details the international standard works on biometrics, especially face recognition, for example, which groups have an interest, what kind of works has been done, and why the standard works are needed. Moreover, the history of MPEG-7 Advanced Face Recognition descriptor and current situations are described. 1 Introduction Biometrics is automatic person recognition method using physiological characteristics. The features in biometrics, for example, are face, iris, fingerprints, voice, retinal, vein, voice and etc. The main reason why the biometric technology is becoming apparent is because the need for the high security is increased these days. Commercially speaking, the recent biometrics is leaded by governments and military which have an ability to make a big market on each purpose. The driver s license with fingerprint is a good example. As the corresponding law is amended, all licenses will be replaced. In biometric technology, face is the most important feature because the face image is remarkably familiar to human beings. When you meet another man in real life, firstly you look at his face and know who he is. The face picture is already in most of identification cards, ex. passport, driving license, and national ID card, which is used to verify user s identity. To give another example, the face image has been a mandatory part in MRTD [1] (Machine Readable Travel Documents), a document containing eye- and machine-readable data and developed by ICAO (International Civil Aviation Organization). Face recognition technology [2] is still developing and many papers are being published. Utilizing face recognition for personal authentication is convenient and more accurate than current method. This is because it is not necessary for user to carry or remember something. In case of old method such as PIN (Personal Identification Number), it is possible that a password can be used by unauthorized person for criminal purpose. Face recognition is no touch biometric technology and does not need expensive equipments. The good example using face recognition is the passport based on encrypted face templates which have an owner s personal characteristic.

2 In a point of view on the performance of face recognition, it is not easy problem which method are the best and which experimental scenarios should be used to measure. FERET [3] and FRVT [4] are useful samples to aim at independent and blind testing the performance of system, but in case of standard work, the one of important things is the interoperability. For this reason the standard works should be opened to the public, but we can not clearly know the operating principles from the result of such blind tests, even though the performance was assured. In this paper we detail foreign organizations which have taking an interest in biometrics as standard works in Section 2. MPEG-7 Advanced Face Recognition descriptor contributed by us and the brief state of affairs is explained in Section 3. 2 Standardization Organizations on Biometrics 2.1 Korean Standardization Organizations In Korea, the representative organizations related to biometrics are TTA (Telecommunications Technology Association) and KATS (Korean Agency for Technology and Standards), the purpose of TTA is to contribute to the advancement of technology and the promotion of information and telecommunications services by effectively establishing and providing technical standards, especially ITU-T and ITU-R, which reflect the latest domestic and international technological advances. Sub Groups 3 (SG3) which focuses on network and system security has a lot of interests in Biometrics. On the other hand, KATS establishes and distributes Korean Industrial Standards (KS) for the provision of industrial technology infrastructure and the protection of consumers. KATS explores and develops standards for new technologies and products according to market demands. They have been supporting a Korean expert group for ISO/IEC JTC1 SC27, SC37 and ISO TC68, relating to Biometrics. Korean standard works already established are K-X9.84, specifying the minimum requirements of security for management of biometric information, and K-BioAPI. 2.2 American Standardization Organization After the tragic events of September 11, demands of biometrics standards are increased in America. NIST (National Institute of Standards and Technology) has played a leading role in biometrics standards and each group supported by NIST has been going to achieve the standard works organically for own purpose. For example, the work of M1-Biometrics Technical Committee in INCITS (InterNational Committee for Information Technology Standards) is to accelerate the deployment of standards-based security solutions for homeland defense and the prevention of identity theft. ANSI/X9F4 Working Group (WG) deals with standardization to reduce financial data security risk and vulnerability and they is developing ANSI X Biometrics Management and Security for the Financial Services Industry which

3 specifies the minimum security requirements for effective management of biometrics data for the financial services industry. BioAPI Consortium, non-governmental group, was formed to develop a widely available and widely accepted API that will serve for various biometric technologies. The remarked standard works are CBEFF (Common Biometric Exchange File Format) defines a common set of data elements necessary to support multiple biometric technologies and BioAPI V1.1, developed by BioAPI Consortium, defines an open system standard API that allows software applications to communicate with a broad range of biometric technologies in a common way. 2.2 International Standardization Organization ISO (International Organization for Standardization) and IEC (International Electrotechnical Commission) form the specialized system for worldwide standardization. National Bodies that are members of ISO or IEC participate in the development of International Standards through technical committees established by the respective organization to deal with particular fields of technical activity. ISO and IEC technical committees collaborate in fields of mutual interest. For standardization in the field of Information Technology, ISO and IEC have established a Joint Technical Committee 1: ISO/IEC JTC 1 on Information Technology whose missions are develop, maintain, promote and facilitate IT standards required by global markets meeting business and user requirements concerning. In this time, there are total 17 subcommittees and SC17, SC27 and SC37 are a close relationship with biometrics. Moreover, SC29- WG11, described in detail afterward, is the only group that has been achieved the standard template on face recognition. (1) ISO/IEC JTC1/SC17 has responsibility for developing standards for identification cards and personal identification. WG (Working Group) 10, motor vehicle driver license and related documents, has been arguing on standards based on biometric information and recently WG11 is organized for biometric standard work in cards. (2) ISO/IEC JTC1/SC27 has been related to standardization of generic methods and techniques for IT Security. The works are biometric data protections techniques, biometric security testing, evaluations, and evaluations methodologies. They has been standardizing on Protection Profile (PP) with Biometrics and Biometrics Evaluation Methodology (BEM). (3) ISO/IEC JTC1/SC37 In June 2002, JTC 1 established a new Subcommittee 37 on Biometrics. The goal of this new JTC 1 SC is to ensure a high priority, focused, and comprehensive approach worldwide for the rapid development and approval of formal international biometric standards. These standards are necessary to support the rapid deployment of significantly better, open systems standard-based security solutions for purposes such as homeland defense and the prevention of ID theft. The scope of SC37 is the standardization of generic biometric technologies pertaining to human beings to support interoperability and data interchange among applications and systems. Generic human biometric standards include: common file frameworks; biometric application programming interfaces; biometric data interchange formats; related biometric profiles; application of evaluation criteria to bio-

4 metric technologies; methodologies for performance testing and reporting and cross jurisdictional and societal aspects. Several fields of SC17, SC27, and SC37 overlap each other in some places and so they have been briskly collaborating in the biometric standard works. SC37 consists of total 6 Working Groups and each mission is as follows; WG1 - Harmonized Biometric Vocabulary, WG2 - Biometric Technical Interfaces, WG3 - Biometric Data Interchange Formats, WG4 - Biometric Functional Architecture and Related Profiles, WG5 - Biometric Testing and Reporting, and WG6 - Cross-Jurisdictional and Societal Aspects. WG3 especially considers the standardization of the content, meaning and representation of biometric data formats which are specific to a particular biometric technology and has been working to ensure a common look and feel for Biometric Data Structure standards, with notation and transfer formats that provide platform independence and separation of transfer syntax from content definition. Such being the case, we are interest in the standard work of WG3 as a scope of face recognition technology. In this time the common format of face picture is a raw image by itself but we can add more the standard format such as the template extracted by face recognition algorithm with a compact size and high performance. In this point, the MPEG-7 Advanced Face Recognition descriptor has been considering now. 3 ISO/IEC JTC1/SC29 WG11 - The Moving Picture Experts Group (MPEG) 3.1 Outline of MPEG The Moving Picture Experts Group (MPEG) [5] is a Working Group (WG11) of ISO/IEC JTC1/SC29 in charge of the development of standards for coded representation of digital audio and video. MPEG-7, the Committee Draft (CD) of the Multimedia Content Description Interface, was issued at the October meeting in This MPEG-7 CD provides a rich source of core technologies which allow the description of audio-visual data content in multimedia environments. During the development of MPEG-7 it was realized that face recognition would be a vital part of the MPEG-7 standard and provide many important functionalities. For this reason it was decided to investigate the extension of the existing face recognition technology in the MPEG-7 CD. 3.2 Objectives of MPEG-7 Face Descriptor There are many applications in which it is desirable to automatically identify a person with MPEG-7 Face Descriptor (FD). Some example applications are: (1) automatic login control by matching an image taken from a built-in camera with a database of users who have authorized access to a computer, (2) using an image taken from a surveillance camera to find any possible matches in a database of known criminals,

5 (3) automatic generation of metadata for creation of personal media libraries, and (4) automatic summarization of video clips based on the identity of the people in the scene. There are also many applications of search and retrieval by face; for example using a frame of a movie which contains a particular actor to locate all other scenes in the movie which contain this same actor. These applications usually involve three stages: location of the face region in the query image, extraction of the face descriptor from the located region and matching the descriptor extracted from the query image with face descriptors present in a database. To determine which method coincides with objectives of face descriptor, participants should submit the document of Core Experiments (CE) at each MPEG meeting. The objectives of CE are (1) to evaluate the retrieval performance of the proposed face descriptors, (2) to evaluate the identification performance of the proposed face descriptors, (3) to evaluate size and computational complexity of the proposed technology (both extraction and matching), (4) to provide cross verification of all results. Thus we should develop a face descriptor with a balance of performance and complexity. 3.3 MPEG-7 Face Descriptor versions 1.0 In the beginning, the 2nd-order eigenfaces [6] is standardized as MPEG-7 FD version 1.0 in The effective features are extracted by 2nd-order eigenface. Selecting different eigen sets made from a residual image, the method can be used for viewangle-invariant and lighting-invariant face description. The 2nd-order eigenfeatures are effective in describing high-passed face image and the 1st-order eigenfeatures are useful in describing the low-passed image. Considering the computing order, the method has the same computational complexity compared with the regular eigenface method [7]. The database is the important fact in face recognition because the performance of face recognition depends on the constitution of the database. In experiments of the 2nd-order eigenface, 1,355 face images of 271 persons are used to examine the performance of lighting-invariant and view-angle-invariant face description. The images are selected from AR (Purdue), AT&T, Yale, UMIST, University of Berne, and some face images obtained from the MPEG-7 news videos. The database is divided into two sections in conformity with CE conditions: One section is to be used for training and the other section is to be used for evaluating the retrieval performance of the algorithms. As a measure of retrieval performance and identification performance, we use ANMRR [8] (Average Normalized Modified Retrieval Rate) and ASR [9] (Average Success Rate), respectively. ANMRR is 0 when all ground truth images are ranked on top, and it is 1 when all ground images are ranked out of the first m images.

6 Fig. 1. Increasing ratios (a) of recognition accuracy and (b) of feature extraction complexity for one year 3.4 MPEG-7 Advanced Face Recognition Descriptor After promotion of MPEG-7 FD version 1.0, MPEG-7 visual group held new CE competition to set up the new FD because the 2nd-order eigenface has not shown the good performance in the extended database. MPEG-7 visual group enlarged the number of face images from 1,355 to 11,845 - it consists of five databases: the extended version 1 MPEG-7 face database, Altkom database, MPEG-7 test set in XM2VTS database, FERET database, and MPEG-7 test set in the BANCA database and also made 8 experimental scenarios - one for Face retrieval, seven for Person Identification. In total, 32 experiments should be performed, which means 8 scenarios (1 Face Image Retrieval+7 Person Identification)*2 training and testing definitions (1:1 and 1:4)*2 clipping sets (manual/automatic eyes detection). Therefore, the condition of new CE is more strict and complex than that of old CE. For one year, 14 or more face recognition algorithms, ex., PCA, ICA, LDA, GDA, NDA and HMM 1, were competed with the extended database and experiments. The performances of new FDs were increased by stages at each MPEG meeting as shown in Fig The reference book on the basic descriptions of recognition algorithms is Pattern Classification written by Duda and etc (John Wiley&Sons).

7 Fig. 2. Extraction of CompositeFeature and CentralCompositeFeature in MPEG-7 AFR. In 2004 we successfully promoted our face recognition algorithm to International Standardization [13] and the recursive matching scheme [10] were also achieved as informative part [11]. The new standardized MPEG-7 Advanced Face Recognition descriptor (AFR) [12] is using Fourier and Intensity LDA features. The descriptor consists of two major parts as shown in Fig. 2; (a) Fourier features of a facial image, (b) extended component features which are enhanced by merging the Fourier features with pose-compensated image intensity features. Twenty four elements of each Fourier feature are mandatory to extract for keeping interoperability in guaranteeing the minimum accuracy at low computational complexity and small memory consumption.

8 The extended features are also defined to achieve the maximum accuracy under unlimited condition of computational complexity and memory consumption. Fig. 3 shows dependency on the number of feature elements to determine the optimal number of each feature. Fig. 3. Dependency on the number of the feature elements in MPEG-7 AFR. 3.5 The Current Issues between SC29 and SC37 on MPEG-7 Advanced Face Recognition Descriptor The MPEG-7 AFR works is a process of defining facial descriptors for searching multimedia contents, but it is not exactly intended to be used for matching and access control as high security. The SC37 biometrics standard work has converged upon a vendor independent face image representation. Because the SC37 group agreed that there does not exist a mature template representation that can be used, in a globally interoperable manner, with the security/access application profiles being developed by ISO and IEC. As a result, the face image format allows for virtually any photo of a face to be captured and stored. And furthermore, the photo image is specific to the frontal face with high quality and under restricted environments [14]. SC37 was not in existence when SC29 began its face recognition work. However, the face recognition work performed by SC29 does clearly fall into the mandate of SC37 as a facial template defined for the purposes of biometric identification. After exchanging the liaison statements between SC29 and SC37, the cooperation has been achieved in July 2004 and we will hope to achieve fruitful results.

9 4 Conclusions This paper presents an introduction of international standardization organization related to biometrics and standard works for facial template, especially MPEG-7 Advanced Face Recognition. An indication of the current substantial growth and interest in biometrics is the emergence of biometrics industry standards and related activities. Standards, especially on face recognition, have become strategic business issues. For any given technology, industry standards assure the availability of multiple sources for comparable products and of competitive products in the marketplace. Standards will support the expansion of the marketplace for biometrics and it will awake many customers interesting in standard works on biometrics. References 1. Biometrics Deployment of Machine Readable Travel Documents, ICAO TAG MRTD/NTWG, May, W. Zhao, R. Chellapa, A. Rosenfeld, and P. Phillips, Face recognition: A literature survey, UMD CfAR Technical Report CAR-TR-948, P. J. Phillips, H. Moon, P. J. Rauss, and S. Rizvi, The FERET evaluation methodology for face recognition algo-rithms, IEEE Transactions on Pattern Analysis and Ma-chine Intelligence, Vol. 22, No. 10, Oct., Face Recognition Vendor Test, 5. R. Koenen, From MPEG-1 to MPEG-21: Creating an Interoperable Multimedia Infrastructure, ISO/IEC JTC1/SC29/WG11 N4518, Dec., L. Wang and T. K. Tan, Experimental results of face description based on the 2nd-order eigenface method, ISO/IEC JTC1/SC29/WG11 M6001, May, M. A. Turk and A. P. Pentland, Eigenfaces for recogni-tion, Journal of Cognitive Neuroscience, Vol. 3, No. 1, pp , B.S. Manjunath, P. Salembier, and T. Sikora, Introduc-tion to MPEG-7: Multimedia Content Description Inter-face, John Wiley & Sons Ltd., M. Bober, Description of MPEG-7 Visual Core Experi-ments, ISO/IEC JTC1/SC29/WG11 N5166, Oct., H. Kim, T. Kim, W. Hwang, S. Kee, "A Recursive Match-ing Method for Content-based Image Retrieval," WIAMIS2004, Portugal, Apr, A. Yamada and L. Cieplinski, MPEG-7 Visual part of experimentation Model Version 18.0, ISO/IEC JTC1/SC29/WG11 N5552, Mar., T. Kamei, A. Yamada, H. Kim, T. Kim, W. Hwang, S. Kee, Advanced Face Descriptor Using Fourier and Inten-sity LDA Features, ISO/IEC JTC1/SC29/WG11 M8998, Oct., L. Cieplinski and A. Yamada, Text of ISO/IEC /FPDAM1, ISO/IEC JTC1/SC29/WG11 N5695, Jul., Biometrics Data Interchange Formats Part 5: Face Image Data, ISO/IEC JTC1/SC37 N506, Mar., 2004.