Series of Dynamic Image Sequences Based on Expression Recognition

To improve the representability of emotion, a joint feature for expression sequences by combining spatial features of single expression image frames was proposed.On the basis of analyzing the representability for identifying expressions with the different combination of rotations and scales to Gabor wavelet, the Gabor filter with three rotations and two scales was adopted to obtain the static image feature.By connecting the feature of series expression images, the joint feature was established by containing the dynamic property of an emotion action.It solved the problem of expression description by using the expression relative local spatial information and the sequential change clues together.Support Vector Machine (SVM) was adopted as the classifier, and the test was done on the JAFFE static expression corpus and Binghamton dynamic expression corpus.Experiments prove the effectiveness of feature with Gabor and PCA comparing to PCA only.Resultsalso show that the joint feature based on dynamic image sequences improve the expression recognition rate referring to static feature.