Abstract
To support the relevant research on face analysis tasks, face image databases with annotated ground-truth are necessary. Although there are many face databases with large amount of images available with increasing research on face analysis, there are few open large face databases with the coordinates of multiple Facial Feature Points (FFPs) provided. In this paper, we build up a large FFP database combining several existing face databases through mapping the known coordinates of the available FFPs to a unified FFP model. The unified model is established based on multiple principles through very thorough analysis of the existing models. The FFPs are mapped to the protocol model with 7 different algorithms. As a result, we obtain a large face database of 70 FFPs labeled with various gender, ethnicity, age and expressions. This new database can be widely used in other relevant researches.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Lucey, P., Cohn, J.F., Kanade, T., Saragih, J., Ambadar, Z., Matthews, I.: The extended cohn-kanade dataset (CK+): A complete dataset for actionunit and emotion-specified expression. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 94–101 (2010)
Wallhoff, F.: Technische Univsität München, http://cotesys.mmk.e-technik.tu-muenchen.de/isg/content/feed-database
Data Tang, http://www.datatang.com/data/45013
Cristinacce, D., Babalola, K.: FGNET Annotation of BioID Dataset, http://personalpages.manchester.ac.uk/staff/timothy.f.cootes/data/bioid_points.html
Cootes, T.: XM2VTS 68pt Markup, http://personalpages.manchester.ac.uk/staff/timothy.f.cootes/data/xm2vts/xm2vts_markup.html
Ding, L., Martinez, A.M.: Features versus Context: An approach forprecise and detailed detection and delineationof faces and facial features. IEEE Pattern Analysis and Machine Intelligence 32(11), 2022–2038 (2010)
Cootes, T.: Talking Face Video (May 2014), http://personalpages.manchester.ac.uk/staff/timothy.f.coo-tes/data/talking_face/talking_face.html
Nordstrm, M.M., Larsen, M., Sierakowski, J., Stegmann, M.B.: The IMM Face Database An Annotated Dataset of 240 Face Images (May 13, 2004)
Cao, X., Wei, Y., Wen, F., Sun, J.: Face alignment by explicit shape regression. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2887–2894. IEEE (2012)
Huang, G.B., Ramesh, M., Berg, T.: Labeled faces in the wild: A database forstudying face recognition in unconstrained environments. Technical report, TechnicalReport 07-49, University of Massachusetts, Amherst (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Gao, P., Fang, Y., Yu, R., Jiang, W. (2014). A Unified Facial Feature Pointdatabase. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-12484-1_16
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12483-4
Online ISBN: 978-3-319-12484-1
eBook Packages: Computer ScienceComputer Science (R0)