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Micro-expression recognition method based on active migration learning

A technology of transfer learning and recognition methods, applied in the field of machine learning and pattern recognition, can solve the problem of small number of database samples and achieve the effect of improving the effect

Active Publication Date: 2018-10-09
SHANDONG UNIV
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Problems solved by technology

In order to give standard micro-expression samples, researchers have spent a lot of time and experience designing induction mechanisms, collecting samples and manually labeling, but the number of existing database samples is still too small

Method used

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  • Micro-expression recognition method based on active migration learning
  • Micro-expression recognition method based on active migration learning
  • Micro-expression recognition method based on active migration learning

Examples

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Embodiment 1

[0099] Such as figure 1 , figure 2 , image 3 As shown, the macro-expression has strong movement range and obvious expression, and can be well recognized in a single frame of pictures; while the micro-expression movement is weak, and needs to be judged with the help of the entire image sequence.

[0100] A micro-expression recognition method based on active transfer learning, such as Figure 4 shown, including:

[0101] Step S1, feature extraction is performed on macro-expression and micro-expression samples. Extract the LBP feature of a single image for the macro-expression sample, and extract the main direction average optical flow feature of the entire image sequence for the micro-expression sample (Main Directional Mean Optical-flow, MDMO, see the paper Liu Y J, Zhang J K, Yan W J, et al. A main directional mean optical flow feature for spontaneous micro-expression recognition[J].IEEE Transactions on Affective Computing,2016,7(4):299-310.)

[0102] In steps S2 and S3...

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Abstract

The invention relates to a micro-expression recognition method based on active migration learning. The method comprises the following steps: (1) extracting micro-expression and micro-expression features; (2) establishing and solving a micro-expression active migration learning problem; (3) recognizing a microexpression. Based on the internal relation between macro expressions and micro expressions, a bridge between macro expressions and micro expressions is constructedthrough an asymmetric linear translator. Less labeled samples are adopted during the initial stage of the active learning. By means of the above translator, the supervision information of the macro-expression domain can be utilized by micro expressions in thetransformation domain. As a result, a high-quality sample can be selected for the active learning in the micro-expression domain. After the sample is manually marked, the sample is added to an existing training set. Therefore, a more effective classifier is obtained through training.

Description

technical field [0001] The invention relates to a micro-expression recognition method based on active transfer learning, which belongs to the technical field of machine learning and pattern recognition. Background technique [0002] Micro-expression is a type of spontaneous expression. It is a natural expression of emotion and an inadvertent expression of emotion, so it cannot be copied and forged. Therefore, it has great application value in the fields of clinical diagnosis and safety precautions. The labeling of micro-expression categories is a demanding task, which requires researchers with a psychological background to combine the context information of the image sequence to give a comprehensive judgment. In order to give standard micro-expression samples, researchers have spent a lot of time and experience designing induction mechanisms, collecting samples and manually labeling, but the number of existing database samples is still too small. [0003] Macro-expressions,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/176G06V40/172G06V40/168G06F18/24G06F18/214
Inventor 贲晛烨李传烨任亿翟鑫亮李梦雅张鑫
Owner SHANDONG UNIV
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