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Spatiotemporal Integration of Optical Flow Vectors for Micro-expression Detection · Study

WorkSpatiotemporal Integration of Optical Flow Vectors for Micro-expression Detection

Devangini Patel2015

Work2015

Spatiotemporal Integration of Optical Flow Vectors for Micro-expression Detection

Devangini Patel · Guoying Zhao · Matti Pietikäinen

62 citations·0/0 files stored·Lecture notes in computer science

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Emotion and Mood Recognition Face recognition and analysis Face and Expression Recognition

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References

1969Nonverbal Leakage and Clues to Deception †2014CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation 2013A Spontaneous Micro-expression Database: Inducement, collection and baseline 2011Recognising spontaneous facial micro-expressions 2013How Fast are the Leaked Facial Expressions: The Duration of Micro-Expressions 2013CASME database: A dataset of spontaneous micro-expressions collected from neutralized faces 2009Facial micro-expressions recognition using high speed camera and 3D-gradient descriptor 1969Nonverbal leakage and clues to deception

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2021Micro-expression spotting: A new benchmark

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2018Micro-expression recognition: an updated review of current trends, challenges and solutionsarticle · 8 shared references 2020Evaluation of the Spatio-Temporal Features and GAN for Micro-Expression Recognition Systemarticle · 8 shared references 2021Video-based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithmsarticle · 7 shared references 2017CAS(ME): A Database for Spontaneous Macro-Expression and Micro-Expression Spotting and Recognitionarticle · 7 shared references 2017Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognitionarticle · 7 shared references 2018A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challengesreview · 7 shared references

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Year2015

Typeother

Published2015-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations62

Files0 public / 0

ShelfEmotion and Mood Recognition

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doi10.1007/978-3-319-25903-1_32

openalex_workW2286400599

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