Face expression identification method based on video time sequence

Abstract

The present invention provides a face expression identification method based on a video time sequence, and relates to the image processing technology field. The method comprises: performing division of image materials obtained after video framing, finding out a complete dynamic expression, employing a face calibration tool to extract the face feature points of each set of expressions, performing geometric normalization processing of the obtained face feature points, calculating the maximum value, the minimum value, the average value, a peak, a skewness, the DFT (Discrete Fourier Transform) peak and the frequency of coordinate sequence of each feature point, employing a PCA (Principal Component Analysis) to perform dimension reduction, remove redundant data, taking as expression feature factors, and finally employing an SVM (Support Vector Machine) or k-NN (k-Nearest Neighbor) to perform learning and identification of the feature vectors to obtain a final expression result. The identification of a learner's dynamic expression is introduced in online learning to identify the most common five expressions such as amazing, carefulness, sleeping, talking and laughing, the identification rate is high, the interaction problem of MOOC (Massive Open Online Course) is effectively solved, and teaching feedback practicality is high in classroom.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for recognizing facial expressions based on video time series. Background technique [0002] Massive Open Online Courses (Massive Open Online Course, referred to as MOOC) is a course form that has emerged rapidly after 2012. It has been highly valued by governments, universities and companies around the world, and has become an important tool to promote "higher education reform". strength. Because traditional face-to-face courses cannot solve the problem of large-scale teaching, technologies such as fragmented teaching video recording and interactive exercises are introduced into MOOC, which makes full use of the fast and convenient characteristics of video transmission to achieve large-scale dissemination of the teaching process, and aims at In order to solve the problem of insufficient teaching feedback caused by one-way video transmission, interactive exerci...

AI Technical Summary

Problems solved by technology

In the application of MOOC courses, many expression states are beyond the traditional six expression modes, such as dozing off, talking, etc. Using many existing expression recognition algorithms in MOOC courses will miss the recognition of some listening states

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