1997
DOI: 10.1109/34.598232
|View full text |Cite
|
Sign up to set email alerts
|

Coding, analysis, interpretation, and recognition of facial expressions

Abstract: We describe a computer vision system for observing facial motion by using an optimal estimation optical flow method coupled with geometric, physical and motion-based dynamic models describing the facial structure.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
378
0
14

Year Published

2000
2000
2017
2017

Publication Types

Select...
4
4
1

Relationship

0
9

Authors

Journals

citations
Cited by 755 publications
(395 citation statements)
references
References 24 publications
1
378
0
14
Order By: Relevance
“…Rigid and deformable tracking of faces and facial features have been a very popular topic of research over the past twenty years (Black and Yacoob 1995;Lanitis et al 1995;Sobottka and Pitas 1996;Essa et al 1996Essa et al , 1997Oliver et al 1997;Decarlo and Metaxas 2000;Jepson et al 2003;Xiao et al 2004;Patras and Pantic 2004;Kim et al 2008;Ross et al 2008;Papandreou and Maragos 2008;Amberg et al 2009;Kalal et al 2010a;Koelstra et al 2010;Tresadern et al 2012;Tzimiropoulos and Pantic 2013;Xiong and De la Torre 2013;Liwicki et al 2013;Smeulders et al 2014;Asthana et al 2014;Li et al 2016a;Xiong and De la Torre 2015;Snape et al 2015;Tzimiropoulos 2015). In this section we provide an overview of face tracking spanning over the past twenty years up to the present day.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Rigid and deformable tracking of faces and facial features have been a very popular topic of research over the past twenty years (Black and Yacoob 1995;Lanitis et al 1995;Sobottka and Pitas 1996;Essa et al 1996Essa et al , 1997Oliver et al 1997;Decarlo and Metaxas 2000;Jepson et al 2003;Xiao et al 2004;Patras and Pantic 2004;Kim et al 2008;Ross et al 2008;Papandreou and Maragos 2008;Amberg et al 2009;Kalal et al 2010a;Koelstra et al 2010;Tresadern et al 2012;Tzimiropoulos and Pantic 2013;Xiong and De la Torre 2013;Liwicki et al 2013;Smeulders et al 2014;Asthana et al 2014;Li et al 2016a;Xiong and De la Torre 2015;Snape et al 2015;Tzimiropoulos 2015). In this section we provide an overview of face tracking spanning over the past twenty years up to the present day.…”
Section: Related Workmentioning
confidence: 99%
“…Deformable tracking of faces can be further subdivided into i) tracking of certain facial landmarks (Lanitis et al 1995;Black and Yacoob 1995;Sobottka and Pitas 1996;Xiao et al 2004;Patras and Pantic 2004;Papandreou and Maragos 2008;Amberg et al 2009;Tresadern et al 2012;Xiong and De la Torre 2013;Asthana et al 2014;Xiong and De la Torre 2015) or ii) tracking/estimation of dense facial motion Yacoob and Davis 1996;Essa et al 1997;Decarlo and Metaxas 2000;Koelstra et al 2010;Snape et al 2015). The latter category of estimating a dense facial motion through a model-based system was proposed by MIT Media lab in mid 1990's (Essa et al 1997Basu et al 1996). In particular, the method by tracks facial motion using optical flow computation coupled with a geometric and a physical (muscle) model describing the facial structure.…”
Section: Prior Artmentioning
confidence: 99%
“…1). In facial expression analysis [67], most systems extract either geometric-based [17] or appearance-based facial features, e.g. Gabor wavelets or local binary patterns [60], to recognise prototypic emotional expressions, such as anger or fear.…”
Section: Intent Profilingmentioning
confidence: 99%
“…One of the problems of fitting a 3D model to a single image is that depth is almost impossible to determine, and the tracking problem is generally underconstrained. As a result, 3D model-based nonrigid motion tracking techniques require either strong prior assumptions about the shape of the object (e.g., symmetry [57], deformable superquadrics [37,40,66], human faces [15,17,56]) or that multiple views of the object are available. By using a 2D deformable image template, the active blobs formulation has the advantage of being able to track general nonrigid motion within the image plane without the need to define a full 3D model nor strong prior assumptions about the shape of the object to be tracked.…”
Section: Related Workmentioning
confidence: 99%