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Minimum -error-based feature extraction method for face microexpression sequence

A feature extraction and micro-expression technology, applied in the field of computer vision, can solve the problems of not forming high-efficiency, high-precision algorithms, etc., and achieve the effect of fast extraction speed

Inactive Publication Date: 2016-05-25
FUDAN UNIV
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AI Technical Summary

Problems solved by technology

However, the current recognition of micro-expressions mainly uses some traditional and general-purpose computer vision technologies for feature extraction and pattern recognition, and no targeted high-efficiency and high-precision algorithms have yet been formed.

Method used

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  • Minimum -error-based feature extraction method for face microexpression sequence
  • Minimum -error-based feature extraction method for face microexpression sequence
  • Minimum -error-based feature extraction method for face microexpression sequence

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Embodiment Construction

[0030] Main contribution of the present invention comprises two points:

[0031] 1. An effective method for extracting micro-expression features is proposed;

[0032] Second, two variants of this feature are proposed.

[0033] These two points are described in detail below.

[0034] 1. Extraction method of micro-expression features

[0035] Segment the face into smaller spatiotemporal blocks, which is based on the following assumptions:

[0036] (1) In a small enough space, the dynamics of micro-expressions are limited by the muscle scale, and their movement patterns (including direction and size) can be regarded as unchanged;

[0037] (2) In a small enough time range, the dynamics of micro-expression is limited by the flexibility of muscle movement, and its movement pattern can be regarded as unchanged.

[0038] We denote it as C(x, y, t) for a particular video block. Since the spatio-temporal block scale is small, it can be considered that the motion patterns of its int...

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Abstract

The invention, which belongs to the technical field of computer vision, particularly relates to a minimum-error-based feature extraction method for face microexpression sequence. A microexpression sequence is segmented into small space-time blocks and a two-dimensional principal direction vector is searched in each space-time block according to a minimum error rule; and principal directions of all blocks are spliced to obtain vectors twice as large as the number dimension of the blocks, thereby representing the overall microexpression sequence. According to the method, the requirement of the uniform frame number in the traditional algorithm is avoided and thus introduction of the interpolation algorithm is not required. Meanwhile, the extraction speed is fast and the possibility of high-precision microexpression detection is provided.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a facial expression feature representation method based on error minimization. Background technique [0002] The current micro-expression recognition mainly uses some traditional and general-purpose computer vision technologies for feature extraction and pattern recognition, but there is no targeted high-efficiency and high-precision algorithm yet. [0003] The invention proposes a new video feature extraction technology, which is mainly used for micro-expression recognition and belongs to the fields of computer vision, image processing and pattern recognition. This method divides the micro-expression sequence into small spatio-temporal blocks, and uses the principle of minimizing the error to extract the motion pattern of the spatio-temporal block as the feature expression of the micro-expression sequence. Experiments show that this method is superior to exi...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V40/175G06V40/168G06V40/172
Inventor 徐峰张军平
Owner FUDAN UNIV
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