The First Facial Landmark Tracking in-the-Wild Challenge: Benchmark and Results

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

41 Citations (Scopus)
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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.
Original languageEnglish
Title of host publication2015 IEEE International Conference on Computer Vision Workshop (ICCVW)
Place of PublicationUSA
PublisherThe Computer Vision Foundation
Pages50-58
Number of pages9
ISBN (Print)978-1-4673-9711-7
DOIs
Publication statusPublished - Dec 2015
EventIEEE International Conference on Computer Vision 2015 - Convention Center in Santiago, Santiago, Chile
Duration: 7 Dec 201513 Dec 2015
http://pamitc.org/iccv15/

Workshop

WorkshopIEEE International Conference on Computer Vision 2015
Abbreviated titleICCV 2015
CountryChile
CitySantiago
Period7/12/1513/12/15
Internet address

Fingerprint

Face recognition
Computer vision
Learning systems
Availability

Keywords

  • EWI-26833
  • HMI-HF: Human Factors
  • METIS-316043
  • EC Grant Agreement nr.: FP7/2007-2013
  • IR-99462
  • EC Grant Agreement nr.: FP7/611153

Cite this

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. In 2015 IEEE International Conference on Computer Vision Workshop (ICCVW) (pp. 50-58). USA: The Computer Vision Foundation. https://doi.org/10.1109/ICCVW.2015.132
Shen, Jie ; Zafeiriou, Stefanos ; Chrysos, Grigorios G. ; Kossaifi, Jean ; Tzimiropoulos, Georgios ; Pantic, Maja. / The First Facial Landmark Tracking in-the-Wild Challenge: Benchmark and Results. 2015 IEEE International Conference on Computer Vision Workshop (ICCVW). USA : The Computer Vision Foundation, 2015. pp. 50-58
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title = "The First Facial Landmark Tracking in-the-Wild Challenge: Benchmark and Results",
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.",
keywords = "EWI-26833, HMI-HF: Human Factors, METIS-316043, EC Grant Agreement nr.: FP7/2007-2013, IR-99462, EC Grant Agreement nr.: FP7/611153",
author = "Jie Shen and Stefanos Zafeiriou and Chrysos, {Grigorios G.} and Jean Kossaifi and Georgios Tzimiropoulos and Maja Pantic",
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Shen, J, Zafeiriou, S, Chrysos, GG, Kossaifi, J, Tzimiropoulos, G & Pantic, M 2015, The First Facial Landmark Tracking in-the-Wild Challenge: Benchmark and Results. in 2015 IEEE International Conference on Computer Vision Workshop (ICCVW). The Computer Vision Foundation, USA, pp. 50-58, IEEE International Conference on Computer Vision 2015, Santiago, Chile, 7/12/15. https://doi.org/10.1109/ICCVW.2015.132

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.

2015 IEEE International Conference on Computer Vision Workshop (ICCVW). USA : The Computer Vision Foundation, 2015. p. 50-58.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AU - Tzimiropoulos, Georgios

AU - Pantic, Maja

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AB - 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.

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KW - METIS-316043

KW - EC Grant Agreement nr.: FP7/2007-2013

KW - IR-99462

KW - EC Grant Agreement nr.: FP7/611153

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DO - 10.1109/ICCVW.2015.132

M3 - Conference contribution

SN - 978-1-4673-9711-7

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EP - 58

BT - 2015 IEEE International Conference on Computer Vision Workshop (ICCVW)

PB - The Computer Vision Foundation

CY - USA

ER -

Shen J, Zafeiriou S, Chrysos GG, Kossaifi J, Tzimiropoulos G, Pantic M. The First Facial Landmark Tracking in-the-Wild Challenge: Benchmark and Results. In 2015 IEEE International Conference on Computer Vision Workshop (ICCVW). USA: The Computer Vision Foundation. 2015. p. 50-58 https://doi.org/10.1109/ICCVW.2015.132