Abstract. In this paper we describe the acquisition and content of a new large, realistic and challenging multi-modal database intended for training and testing multi-modal verification systems. The BANCA database was captured in four European languages in two modalities (face and voice). For recording, both high and low quality microphones and cameras were used. The subjects were recorded in three different scenarios, controlled, degraded and adverse over a period of three months. In total 208 people were captured, half men and half women. In this paper we also describe a protocol for evaluating verification algorithms on the database. The database will be made available to the research community through http://www.ee.surrey.ac.uk/Research/VSSP/banca.

We present a novel method for localizing faces in person identification scenarios. Such scenarios involve high resolution images of frontal faces. The proposed algorithm does not require color, copes well in cluttered backgrounds, and accurately localizes faces including eye centers. An extensive analysis and a performance evaluation on the XM2VTS database and on the realistic BioID and BANCA face databases is presented. We show that the algorithm has precision superior to reference methods.

The paper presents results of the face verification contest that was organized in conjunction with International Conference on Pattern Recognition 2000 [14]. Participants had to use identical data sets from a large, publicly available multimodal database XM2VTSDB. Training and evaluation was carried out according to an a priori known protocol ([7]). Verification results of all tested algorithms have been collected and made public on the XM2VTSDB website [15], facilitating large scale experiments on classifier combination and fusion. Tested methods included, among others, representatives of the most common approaches to face verificationelastic graph matching, Fisher's linear discriminant and Support vector machines.

This paper details the results of a Face Authentication Test (FAT2004) [5] held in conjunction with the 17th International Conference on Pattern Recognition. The contest was held on the publicly available BANCA database [1] according to a defined protocol [7]. The competition also had a sequestered part in which institutions had to submit their algorithms for independent testing. 13 different verification algorithms from 10 institutions submitted results. Also, a standard set of face recognition software packages from the Internet [2] were used to provide a baseline performance measure.

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