Commercial application of facial recognition demands robustness to a variety of challenges such as illumination, occlusion, spoofing, disguise, etc. Disguised face recognition is one of the emerging issues for access control systems, such as security checkpoints at the borders. However, the lack of availability of face databases with a variety of disguise add-ons limits the development of academic research in the area. In this paper, we present a multi-modal disguised face dataset to facilitate the disguised face recognition research. The presented database contains 8 facial add-ons and 7 additional combinations of these add-ons to create a variety of disguised face images. Each facial image is captured in visible, visible plus infrared, infrared, and thermal spectra. Specifically, the database contains 100 subjects divided into Subset-A (30 subjects, 1 image per modality) and Subset-B (70 subjects, 5 plus images per modality). We also present baseline face detection results performed on the proposed database to provide reference results and compare the performance in different modalities. Qualitative and quantitative analysis is performed to evaluate the challenging nature of disguise add-ons. The dataset will be publicly available with the acceptance of the research article.

面部识别的商业应用要求鲁棒性应对各种挑战，例如照明，遮挡，欺骗，伪装等。伪装的面部识别是访问控制系统（如边界安全检查站）的新兴问题之一。然而，缺乏具有各种伪装附件的面部数据库的可用性限制了该领域的学术研究的发展。在本文中，我们提出了一种多模式变相人脸数据集，以促进变相人脸识别研究。呈现的数据库包含8个面部附加组件和这些附加组件的7个其他组合，以创建各种伪装的面部图像。每个面部图像都以可见光，可见光以及红外，红外和热光谱捕获。具体来说，数据库包含100个主题，分为A组（30个主题，每个模态1个图像）和B组（70个主题，每个模态5个图像）。我们还将介绍在建议的数据库上执行的基准人脸检测结果，以提供参考结果并比较不同模式下的性能。进行定性和定量分析以评估伪装附件的挑战性。该数据集将在研究文章被接受后公开提供。