Depth information has been proved to be very effective in Image Processing community and with the popularity of Kinect since its introduction, RGB-D has been explored extensively for various applications. Therefore, the need for the development of Kinect image & video database is crucial.
Here, our effort is to create a Kinect Face database of images of different facial expressions in different lighting and occlusion conditions to serve various research purposes.
The structure of the database is illustrated in the following hierarchy [figure 4]
Any publication using this database must cite the following paper
Rui Min, Neslihan Kose, Jean-Luc Dugelay, “KinectFaceDB: A Kinect Database for Face Recognition,” Systems, Man, and Cybernetics: Systems, IEEE Transactions on , vol.44, no.11, pp.1534,1548, Nov. 2014, doi: 10.1109/TSMC.2014.2331215
@ARTICLE{IEEETransactions,
author={Rui Min and Neslihan Kose and Jean-Luc Dugelay},
journal={Systems, Man, and Cybernetics: Systems, IEEE Transactions on},
title={KinectFaceDB: A Kinect Database for Face Recognition},
year={2014},
month={Nov},
volume={44},
number={11},
pages={1534-1548},
doi={10.1109/TSMC.2014.2331215},
ISSN={2168-2216},}
Interested researchers can refer to the Florence Superface Dataset at http://www.micc.unifi.it/vim/datasets/4d-faces/, in order to test their algorithms on a separate dataset, and thus use diverse sets for training and test.
support
If you have any question or request regarding the EURECOM Kinect Face Dataset, please contact Prof. Jean-Luc DUGELAY via jld@eurecom.fr