A comprehensive performance evaluation of deformable face tracking “In-the-Wild”
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Supporting information
Published version
Author(s)
Chrysos, GG
Antonakos, E
Snape, P
Asthana, A
Zafeiriou, S
Type
Journal Article
Abstract
Recently, technologies such as face detection, facial landmark localisation and face recognition and verification have matured enough to provide effective and efficient solutions for imagery captured under arbitrary conditions (referred to as “in-the-wild”). This is partially attributed to the fact that comprehensive “in-the-wild” benchmarks have been developed for face detection, landmark localisation and recognition/verification. A very important technology that has not been thoroughly evaluated yet is deformable face tracking “in-the-wild”. Until now, the performance has mainly been assessed qualitatively by visually assessing the result of a deformable face tracking technology on short videos. In this paper, we perform the first, to the best of our knowledge, thorough evaluation of state-of-the-art deformable face tracking pipelines using the recently introduced 300 VW benchmark. We evaluate many different architectures focusing mainly on the task of on-line deformable face tracking. In particular, we compare the following general strategies: (a) generic face detection plus generic facial landmark localisation, (b) generic model free tracking plus generic facial landmark localisation, as well as (c) hybrid approaches using state-of-the-art face detection, model free tracking and facial landmark localisation technologies. Our evaluation reveals future avenues for further research on the topic.
Date Issued
2017-02-25
Date Acceptance
2017-02-10
Citation
International Journal of Computer Vision, 2017, 126 (2-4), pp.198-232
ISSN
0920-5691
Publisher
Springer Verlag
Start Page
198
End Page
232
Journal / Book Title
International Journal of Computer Vision
Volume
126
Issue
2-4
Copyright Statement
© The Author(s) 2017.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Commission of the European Communities
Grant Number
EP/L026813/1
EP/N007743/1
688520
Subjects
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science
Deformable face tracking
Face detection
Model free tracking
Facial landmark localisation
Long-term tracking
ACTIVE APPEARANCE MODELS
3-D MOTION ESTIMATION
VISUAL TRACKING
OBJECT TRACKING
PICTORIAL STRUCTURES
FACIAL EXPRESSIONS
COMPONENT ANALYSIS
IMAGE SEQUENCES
POSE ESTIMATION
OPTICAL-FLOW
cs.CV
cs.AI
0801 Artificial Intelligence And Image Processing
Artificial Intelligence & Image Processing
Publication Status
Published