Recovering joint and individual components in facial data
File(s)
Accepted version
Author(s)
Sagonas
Ververas
Panagakis
Zafeiriou, S
Type
Journal Article
Abstract
A set of images depicting faces with different expressions or in various ages consists of components that are shared across all images (i.e., joint components) imparting to the depicted object the properties of human faces as well as individual components that are related to different expressions or age groups. Discovering the common (joint) and individual components in facial images is crucial for applications such as facial expression transfer and age progression. The problem is rather challenging when dealing with images captured in unconstrained conditions in the presence of sparse non-Gaussian errors of large magnitude (i.e., sparse gross errors or outliers) and contain missing data. In this paper, we investigate the use of a method recently introduced in statistics, the so-called Joint and Individual Variance Explained (JIVE) method, for the robust recovery of joint and individual components in visual facial data consisting of an arbitrary number of views. Since the JIVE is not robust to sparse gross errors, we propose alternatives, which are (1) robust to sparse gross, non-Gaussian noise, (2) able to automatically find the individual components rank, and (3) can handle missing data. We demonstrate the effectiveness of the proposed methods to several computer vision applications, namely facial expression synthesis and 2D and 3D face age progression ‘in-the-wild’.
Date Issued
2018-11-01
Date Acceptance
2017-10-05
Citation
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40 (11), pp.2668-2681
ISSN
0162-8828
Publisher
Institute of Electrical and Electronics Engineers
Start Page
2668
End Page
2681
Journal / Book Title
IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume
40
Issue
11
Copyright Statement
© 2017 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.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Grant Number
EP/J017787/1
EP/N007743/1
Subjects
Science & Technology
Technology
Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Computer Science
Engineering
Low-rank
sparsity
facial expression synthesis
face age progression
joint and individual components
SYSTEMS
FACES
SETS
0801 Artificial Intelligence And Image Processing
0806 Information Systems
0906 Electrical And Electronic Engineering
Artificial Intelligence & Image Processing
Publication Status
Published
Date Publish Online
2017-12-18