A semi-automatic methodology for facial landmark annotation

Sagonas, Christos; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

Abstract

Developing powerful deformable face models requires massive, annotated face databases on which techniques can be trained, validated and tested. Manual annotation of each facial image in terms of landmarks requires a trained expert and the workload is usually enormous. Fatigue is one of the reasons that in some cases annotations are inaccurate. This is why, the majority of existing facial databases provide annotations for a relatively small subset of the training images. Furthermore, there is hardly any correspondence between the annotated landmarks across different databases. These problems make cross-database experiments almost infeasible. To overcome these difficulties, we propose a semi-automatic annotation methodology for annotating massive face datasets. This is the first attempt to create a tool suitable for annotating massive facial databases. We employed our tool for creating annotations for MultiPIE, XM2VTS, AR, and FRGC Ver. 2 databases. The annotations will be made publicly available from http://ibug.doc.ic.ac.uk/ resources/facial-point-annotations/. Finally, we present experiments which verify the accuracy of produced annotations.

Citation

Sagonas, C., Tzimiropoulos, G., Zafeiriou, S., & Pantic, M. (2013). A semi-automatic methodology for facial landmark annotation.

• Conference Name: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPRW)
• Start Date: Jun 23, 2013
• End Date: Jun 28, 2013
• Publication Date: Jun 1, 2013
• Deposit Date: Jan 29, 2016
• Publicly Available Date: Mar 7, 2019
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Keywords: Face recognition, Image retrieval, Visual databases
• Public URL: https://nottingham-repository.worktribe.com/output/1002059
• Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6595977&newsearch=true&queryText=semi-automatic%20methodology%20for%20facial%20landmark%20annotation
• Additional Information: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.