MOBIO is a bi-modal database that was captured almost exclusively on mobile phones. It aims to improve research into deploying biometric techniques to mobile devices. Research has been shown that face and speaker recognition can be performed in a mobile environment. Facial landmark localization aims at finding the coordinates of a set of pre-defined key points for 2D face images. A facial landmark usually has specific semantic meaning, e.g. nose tip or eye centre, which provides rich geometric information for other face analysis tasks such as face recognition, emotion estimation and 3D face reconstruction. Pretty much facial landmark detection methods adopt still face databases, such as 300W, AFW, AFLW, or COFW, for evaluation, but seldomly use mobile data. Our work is first to perform facial landmark detection evaluation on the mobile still data, i.e., face images from MOBIO database. About 20,600 face images have been extracted from this audio-visual database and manually labeled with 22 landmarks as the groundtruth. Several state-of-the-art facial landmark detection methods are adopted to evaluate their performance on these data. The result shows that the data from MOBIO database is pretty challenging. This database can be a new challenging one for facial landmark detection evaluation.

翻译：MOBIO是一个几乎完全在手机上捕获的双模态数据库，旨在推动将生物识别技术部署到移动设备上的研究。研究表明，在移动环境中可以执行人脸和说话人识别。人脸关键点定位旨在寻找二维人脸图像中一组预定义关键点的坐标。人脸关键点通常具有特定的语义含义，例如鼻尖或眼睛中心，这为其他人脸分析任务（如人脸识别、情绪估计和三维人脸重建）提供了丰富的几何信息。目前，大多数人脸关键点检测方法采用静止人脸数据库（如300W、AFW、AFLW或COFW）进行评估，但很少使用移动数据。我们的工作是首次在移动静止数据（即来自MOBIO数据库的人脸图像）上执行人脸关键点检测评估。从该音视频数据库中提取了约20600张人脸图像，并人工标注了22个关键点作为真实值。采用了几种最先进的人脸关键点检测方法来评估它们在这些数据上的性能。结果表明，MOBIO数据库中的数据相当具有挑战性。该数据库可成为人脸关键点检测评估的新挑战性基准。