Automatic expression spotting in videos

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Cite
Shreve, Matthew, et al. “Automatic Expression Spotting in Videos”. Image and Vision Computing, vol. 32, no. 8, 2014, pp. 476-8, https://doi.org/10.1016/j.imavis.2014.04.010.
Shreve, M., Brizzi, J., Fefilatyev, S., Luguev, T., Goldgof, D., & Sarkar, S. (2014). Automatic expression spotting in videos. Image and Vision Computing, 32(8), 476-486. https://doi.org/10.1016/j.imavis.2014.04.010
Shreve, Matthew, Jesse Brizzi, Sergiy Fefilatyev, Timur Luguev, Dmitry Goldgof, and Sudeep Sarkar. “Automatic Expression Spotting in Videos”. Image and Vision Computing 32, no. 8 (2014): 476-86. https://doi.org/10.1016/j.imavis.2014.04.010.
Shreve M, Brizzi J, Fefilatyev S, Luguev T, Goldgof D, Sarkar S. Automatic expression spotting in videos. Image and Vision Computing. 2014;32(8):476-8.
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DISFA: a spontaneous facial action intensity database IEEE Transactions on Affective Computing 2013
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  • Technology: Engineering (General). Civil engineering (General)
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Facial expression recognition based on Local Binary Patterns: A comprehensive study Image and Vision Computing
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Citations
Title Journal Journal Categories Citations Publication Date
SFAMNet: A scene flow attention-based micro-expression network Neurocomputing
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 2024
Micro-expression spotting with a novel wavelet convolution magnification network in long videos Pattern Recognition Letters
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 2024
LAENet for micro-expression recognition The Visual Computer
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  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 2 2023
Lite general network and MagFace CNN for micro-expression spotting in long videos Multimedia Systems
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Micro-expressions: a survey Multimedia Tools and Applications
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Citations Analysis
Category Category Repetition
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics11
Science: Mathematics: Instruments and machines: Electronic computers. Computer science10
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks8
Technology: Mechanical engineering and machinery6
Technology: Engineering (General). Civil engineering (General)6
Science: Science (General): Cybernetics: Information theory5
Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software4
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware4
Science: Physics1
Technology: Manufactures: Production management. Operations management1
Philosophy. Psychology. Religion: Psychology1
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system: Psychiatry1
The category Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics 11 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Hybrid Facial Regions Extraction for Micro-expression Recognition System and was published in 2017. The most recent citation comes from a 2024 study titled Micro-expression spotting with a novel wavelet convolution magnification network in long videos. This article reached its peak citation in 2023, with 6 citations. It has been cited in 12 different journals, 8% of which are open access. Among related journals, the Neurocomputing cited this research the most, with 3 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year