Micro expression sequence feature extracting method based on optical flow field

Abstract

The invention belongs to the technical field of computer visions, in particular a micro expression sequence feature extracting method based on an optical flow field. The method comprises the following steps: firstly extracting a dense optical flow field between adjacent frames in the premise that the frame number of the micro expression is fixed; eliminating the influence of the human face translation to the micro expression recognition through fine alignment; and then segmenting the aligned optical flow fields into a series of space-time sub-blocks, extracting a main direction in each space-time sub-block to represent the motion pattern of majority points in the sub-block; quantizing and splicing main directions in all sub-blocks, and expressing in a vector form, namely obtaining the designed micro expression sequence feature. The novel feature based on the motion description provided by the invention can be used for the micro expression recognition. Through the adoption of the method disclosed by the invention, the comprehensive indexes such as accuracy, precision and recalling rate are superior to other existing methods, and the further development of the micro expression recognition technology is promoted; and meanwhile, the method is capable of depicting the dynamic pattern of the micro expression and providing deeper understanding for the analysis of the micro expression.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a micro-expression sequence feature extraction method based on an optical flow field. Background technique [0002] At present, there are many difficulties in micro-expression recognition, and practical methods and theoretical frameworks have not yet been formed at this stage. Its difficulty is mainly manifested in feature extraction. The currently used features are often general-purpose video feature expressions, which are not optimized for the application of micro-expressions, nor can they provide a deep understanding of micro-expressions. [0003] Microexpressions were first discovered in 1969 when psychologists observed videotaped conversations with depressed patients [1]. The patients in the video often show a normal smile, however, a few frames of abnormally distressed expressions can be found. Psychologists call them microexpressions. [0004] Unlik...

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Problems solved by technology

However, micro-expression analysis has high requirements for fine alignment of faces, and this method cannot handle this problem well.

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