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The first Facial Landmark Tracking in-the-Wild Challenge: benchmark and results

Shen, Jie; Zafeiriou, Stefanos; Chrysos, Grigorios G.; Kossaifi, Jean; Tzimiropoulos, Georgios; Pantic, Maja

Authors

Jie Shen

Stefanos Zafeiriou

Grigorios G. Chrysos

Jean Kossaifi

Georgios Tzimiropoulos

Maja Pantic



Abstract

Detection and tracking of faces in image sequences is among the most well studied problems in the intersection of statistical machine learning and computer vision. Often, tracking and detection methodologies use a rigid representation to describe the facial region 1, hence they can neither capture nor exploit the non-rigid facial deformations, which are crucial for countless of applications (e.g., facial expression analysis, facial motion capture, high-performance face recognition etc.). Usually, the non-rigid deformations are captured by locating and tracking the position of a set of fiducial facial landmarks (e.g., eyes, nose, mouth etc.). Recently, we witnessed a burst of research in automatic facial landmark localisation in static imagery. This is partly attributed to the availability of large amount of annotated data, many of which have been provided by the first facial landmark localisation challenge (also known as 300-W challenge). Even though now well established benchmarks exist for facial landmark localisation in static imagery, to the best of our knowledge, there is no established benchmark for assessing the performance of facial landmark tracking methodologies, containing an adequate number of annotated face videos. In conjunction with ICCV’2015 we run the first competition/challenge on facial landmark tracking in long-term videos. In this paper, we present the first benchmark for long-term facial landmark tracking, containing currently over 110 annotated videos, and we summarise the results of the competition.

Publication Date Dec 1, 2015
Peer Reviewed Peer Reviewed
APA6 Citation Shen, J., Zafeiriou, S., Chrysos, G. G., Kossaifi, J., Tzimiropoulos, G., & Pantic, M. (2015). The first Facial Landmark Tracking in-the-Wild Challenge: benchmark and results
Publisher URL http://www.cv-foundation.org/openaccess/content_iccv_2015_workshops/w25/html/Shen_The_First_Facial_ICCV_2015_paper.html
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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