基于高分辨率距离的人脸数据库免费

Context Face database composed by a set of high resolution range images acquired by the latest generation of range / depth cameras: the Microsoft Kinect 2 (second generation). Content The database is composed by the faces of 18 people, acquired from different poses: frontal, lateral, etc. Faces have been acquired with and without glasses. The database is structured in different folders as: * /01: person with identifier 01. * /01/test: images for testing the person with identifier 01. * /01/test/01_009.png, ..., 03_096.png, ...: images starting with the same identifier as the root folder (01 in this case) are the true/positive samples, while the others are the false/negative samples. * /01/train: images for training the person with identifier 01. * /01/train/01_034.png, ..., 05_g_168.png, ...: images starting with the same identifier as the root folder (01 in this case= are the true/positive samples, while the others are the false/negative samples. * /02 * /03 * /04 * /04_g: same person as /04, but with glasses. * /05 * ... * /18 Every root folder (01, 02, ...) contains the depth images of one person. The folder name is the identifier of the person (for example 01, 02, etc.). Inside every root folder, there are two sub-folders: test (for testing purposes) and train (for training purposes). Citation T. Mantecón, C.R. del Blanco, F. Jaureguizar, N. García, “Visual Face Recognition using Bag of Dense Derivative Depth Patterns“, IEEE Signal Processing Letters, vol. 23, no. 6, pp. 771-775, June 2016. (doi: 10.1109/LSP.2016.2553784)