Robust Registration of Dynamic Facial Sequences.

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TitleRobust Registration of Dynamic Facial Sequences.
Publication TypeJournal Article
Year of Publication2017
AuthorsSariyanidi, E, Gunes, H, Cavallaro, A
JournalIEEE Trans Image Process
Volume26
Issue4
Pagination1708-1722
Date Published2017 Apr
ISSN1941-0042
KeywordsAlgorithms, Databases, Factual, Face, Facial Expression, Female, Humans, Image Processing, Computer-Assisted, Male
Abstract

Accurate face registration is a key step for several image analysis applications. However, existing registration methods are prone to temporal drift errors or jitter among consecutive frames. In this paper, we propose an iterative rigid registration framework that estimates the misalignment with trained regressors. The input of the regressors is a robust motion representation that encodes the motion between a misaligned frame and the reference frame(s), and enables reliable performance under non-uniform illumination variations. Drift errors are reduced when the motion representation is computed from multiple reference frames. Furthermore, we use the L norm of the representation as a cue for performing coarse-to-fine registration efficiently. Importantly, the framework can identify registration failures and correct them. Experiments show that the proposed approach achieves significantly higher registration accuracy than the state-of-the-art techniques in challenging sequences.

DOI10.1109/TIP.2016.2639448
Alternate JournalIEEE Trans Image Process
PubMed ID28055877