FARO: FAce Recognition Against Occlusions and Expression Variations
FARO: FAce Recognition Against Occlusions and Expression Variations
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DOI：
10.1109/tsmca.2009.2033031
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发表时间：
2010-01-01
影响因子：
--
通讯作者：
Riccio, Daniel
中科院分区：
文献类型：
--
作者：
De Marsico, Maria;Nappi, Michele;Riccio, Daniel
人脸识别被广泛认为是最有前途的生物识别技术之一，它可以在不太具侵入性的情况下实现高识别率。已经提出了许多方法来解决这一特殊的模式识别问题，也解决了人脸变化的挑战性情况，主要发生在表情、光照或姿势上。另一方面，在涉及部分遮挡(即太阳镜和围巾)的文献中可以找到的工作较少。本文提出了一种基于分区迭代函数系统(PIFS)的人脸识别方法--抗遮挡和表情变化(FARO)方法，该方法对表情变化和部分遮挡具有较强的鲁棒性。一般来说，基于PIFSS的算法计算整个输入图像内部的自相似映射，搜索小正方形区域之间的对应关系。然而，这类传统算法会受到遮挡等局部失真的影响。为了克服这种限制，PIF提取的信息通过在每个面部组件(眼睛、鼻子和嘴巴)上独立工作来实现局部化。由可能的遮挡或表情变化引入的失真通过自组织距离测量被进一步减少。为了从实验上证实该方法对光照变化、表情变化以及遮挡的稳健性，使用AR人脸数据库对Faro进行了测试，AR-Faces数据库是科学界在这方面的主要基准之一。在人脸识别大挑战数据库上的实验结果进一步验证了FARO的性能。
Face recognition is widely considered as one of the most promising biometric techniques, allowing high recognition rates without being too intrusive. Many approaches have been presented to solve this special pattern recognition problem, also addressing the challenging cases of face changes, mainly occurring in expression, illumination, or pose. On the other hand, less work can be found in literature that deals with partial occlusions (i.e., sunglasses and scarves). This paper presents FAce Recognition against Occlusions and Expression Variations (FARO) as a new method based on partitioned iterated function systems (PIFSs), which is quite robust with respect to expression changes and partial occlusions. In general, algorithms based on PIFSs compute a map of self-similarities inside the whole input image, searching for correspondences among small square regions. However, traditional algorithms of this kind suffer from local distortions such as occlusions. To overcome such limitation, information extracted by PIFS is made local by working independently on each face component (eyes, nose, and mouth). Distortions introduced by likely occlusions or expression changes are further reduced by means of an ad hoc distance measure. In order to experimentally confirm the robustness of the proposed method to both lighting and expression variations, as well as to occlusions, FARO has been tested using AR-Faces database, one of the main benchmarks for the scientific community in this context. A further validation of FARO performances is provided by the experimental results produced on Face Recognition Grand Challenge database.