Face recognition finds its place in a large number of applications. They occur in different contexts related to security, entertainment or Internet applications. Reliable face recognition is still a great challenge to computer vision and pattern recognition researchers, and new algorithms need to be evaluated on relevant databases. The publicly available IV2 database allows monomodal and multimodal experiments using face data. Known variabilities, that are critical for the performance of the biometric systems (such as pose, expression, illumination and quality) are present. The face and subface data that are acquired in this database are: 2D audio-video talking-face sequences, 2D stereoscopic data acquired with two pairs of synchronized cameras, 3D facial data acquired with a laser scanner, and iris images acquired with a portable infrared camera. The IV2 database is designed for monomodal and multimodal experiments. The quality of the acquired data is of great importance. Therefore as a first step, and in order to better evaluate the quality of the data, a first internal evaluation was conducted. Only a small amount of the total acquired data was used for this evaluation: 2D still images, 3D scans and iris images. First results show the interest of this database. In parallel to the research algorithms, open-source reference systems were also run for baseline comparisons.
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机译:面部识别在大量应用中找到了它的位置。它们发生在与安全性,娱乐或互联网应用程序相关的不同环境中。可靠的人脸识别对计算机视觉和模式识别研究人员来说仍然是一个巨大的挑战,并且需要在相关数据库上进行新的算法。可公开的IV 2 sup>数据库允许使用面部数据的单峰和多模态实验。存在对生物识别系统的性能至关重要的已知变形性(例如姿势,表达,照明和质量)。在该数据库中获取的面部和副表数据是:2D音频 - 视频通信面序列,用两对同步摄像机获取的2D立体数据,用激光扫描仪获取的3D面部数据,以及使用便携式红外获取的虹膜图像相机。 IV 2 sup>数据库专为单兆位和多模式实验而设计。获得数据的质量非常重要。因此,作为第一步,并且为了更好地评估数据的质量,进行了第一内部评估。只有少量的获取数据用于此评估:2D静止图像,3D扫描和虹膜图像。第一个结果显示此数据库的兴趣。与研究算法并行,也运行开源参考系统以进行基线比较。
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