Military Electrical and Computer Engineering, Portuguese Military Academy, Rua Gomes Freire, 1169-203 Lisbon, Portugal.
Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal.
Sensors (Basel). 2022 Jun 1;22(11):4219. doi: 10.3390/s22114219.
This work proposes a multi-spectral face recognition system in an uncontrolled environment, aiming to identify or authenticate identities (people) through their facial images. Face recognition systems in uncontrolled environments have shown impressive performance improvements over recent decades. However, most are limited to the use of a single spectral band in the visible spectrum. The use of multi-spectral images makes it possible to collect information that is not obtainable in the visible spectrum when certain occlusions exist (e.g., fog or plastic materials) and in low- or no-light environments. The proposed work uses the scores obtained by face recognition systems in different spectral bands to make a joint final decision in identification. The evaluation of different methods for each of the components of a face recognition system allowed the most suitable ones for a multi-spectral face recognition system in an uncontrolled environment to be selected. The experimental results, expressed in Rank-1 scores, were 99.5% and 99.6% in the TUFTS multi-spectral database with pose variation and expression variation, respectively, and 100.0% in the CASIA NIR-VIS 2.0 database, indicating that the use of multi-spectral images in an uncontrolled environment is advantageous when compared with the use of single spectral band images.
本工作提出了一种在非受控环境中的多光谱人脸识别系统，旨在通过面部图像识别或验证身份（人）。 近几十年来，非受控环境中的人脸识别系统在性能方面取得了令人瞩目的进步。 然而，大多数系统仅限于使用可见光谱中的单个光谱带。 多光谱图像的使用使得在存在某些遮挡（例如雾或塑料材料）和低光照或无光照环境时，能够收集在可见光谱中不可获得的信息成为可能。 所提出的工作使用在不同光谱带中的人脸识别系统获得的分数来做出识别的联合最终决策。 对人脸识别系统的每个组件的不同方法进行评估，选择了最适合非受控环境中的多光谱人脸识别系统的方法。 在 TUFT 多光谱数据库中，分别在存在姿态变化和表情变化的情况下，实验结果表示为 Rank-1 分数，分别为 99.5%和 99.6%，在 CASIA NIR-VIS 2.0 数据库中，为 100.0%，表明与使用单光谱带图像相比，在非受控环境中使用多光谱图像具有优势。
