Method for recognizing human face micro-expressions in video sequence

A technology of video sequence and recognition method, which is applied in the direction of character and pattern recognition, instruments, computer components, etc., and can solve the problems of low recognition performance, single micro-expression sequence information, and high computational complexity

Active Publication Date: 2015-12-09
HEBEI UNIV OF TECH
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Problems solved by technology

CN103258204A discloses a kind of automatic micro-expression recognition method based on Gabor and EOH feature, utilizes Gabor and EOH feature to carry out micro-expression feature extraction, but the ability of Gabor and EOH to represent the whole situation is weak, and needs to be combined with the improved GentleSVM classifier to carry out The classification and recognition of micro-expressions requires high performance requirements of hardware equipment, but the recognition performance is lower than people's expectations
CN104298981A proposes an automatic micro-expression reco

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  • Method for recognizing human face micro-expressions in video sequence
  • Method for recognizing human face micro-expressions in video sequence
  • Method for recognizing human face micro-expressions in video sequence

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Embodiment 1

[0090] The recognition method of human face micro-expression in the video sequence of the present embodiment is a kind of dynamic spatiotemporal texture characteristic method that utilizes HLACLF-TOP algorithm to extract human face micro-expression sequence, concrete steps are as follows:

[0091] In the first step, the face micro-expression video Euler zooms in:

[0092] Use the Euler image magnification algorithm to amplify the face micro-expression video, and convert the amplified human face micro-expression video into a human face micro-expression image sequence; the effect of the face micro-expression video before and after this step is as follows: figure 2 As shown in the examples;

[0093] The second step, face micro-expression image preprocessing:

[0094] Use the Gaussian filter to denoise the face micro-expression image sequence obtained in the first step, use the Adaboost algorithm to detect and crop the face in the micro-expression image, and use the bilinear int...

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Abstract

The invention discloses a method for recognizing human face micro-expressions in a video sequence and relates to the treatment on a recording carrier for recognized patterns. A method for the extracting dynamic spatial-temporal textural characteristics of human face micro-expression sequences based on the HLACLF-TOP algorithm is provided. The method comprises the steps of amplifying the video of human face micro-expressions based on the Euler function, preprocessing the images of human face micro-expressions, extracting the dynamic spatial-temporal textural characteristics of human face micro-expression sequences based on the HLACLF-TOP algorithm, training and predicting by utilizing an ELM classifier. Based on the above method, the defect in the prior art that human face micro-expressions are hard to recognize due to the small variation amplitude of human face micro-expressions can be overcome.

Description

technical field [0001] The technical solution of the present invention relates to the processing of a record carrier for recognizing graphics, in particular to the recognition method of human facial micro-expressions in a video sequence. Background technique [0002] Micro-expression (micro-expression) is a very short-lived uncontrollable facial expression revealed by humans when they try to suppress or hide their true emotions. Ekman et al. conducted a series of studies on micro-expression, and the results showed that micro-expression is an effective way to identify lies. Clues can be widely used in security, judicial, clinical and legal fields. However, micro-expressions are short-lived and difficult to recognize. Even with well-trained people, the accuracy rate of micro-expression recognition is only about 40%. Therefore, it is very necessary to develop an automatic micro-expression recognition system and realize computer automatic recognition of micro-expressions, both ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/00G06K9/46
CPCG06V40/176G06V20/46G06V10/462G06F18/2411
Inventor 郭迎春于洋阎刚师硕刘依张满囤李聪慧
Owner HEBEI UNIV OF TECH
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