A shielded expression recognition algorithm combining double dictionaries and an error matrix

Abstract

The invention discloses a shielded expression recognition algorithm combining double dictionaries and an error matrix, which comprises the following steps of: firstly, separating expression characteristics and identity characteristics in each type of expression images by utilizing low-rank decomposition, and respectively carrying out dictionary learning on a low-rank matrix and a sparse matrix toobtain an intra-class related dictionary and a difference structure dictionary; Secondly, when the shielded images are classified, original sparse coding does not consider coding errors, the coding errors caused by shielding cannot be accurately described, it is proposed that the errors caused by shielding are expressed by a single matrix, and the matrix can be separated from a feature matrix of the unshielded training image; a clear image can be recovered by subtracting the error matrix from the test sample; a clear image sample is decomposed into identity features and expression features ina low-rank manner by using double-dictionary cooperative representation, and finally classification is realized according to contribution of each type of expression features in joint sparse representation. The method has robustness for random shielding expression recognition.

Description

technical field [0001] The present invention relates to the field of image processing, and more specifically, relates to an occlusion expression recognition algorithm that combines a double dictionary and an error matrix. Background technique [0002] Facial expression recognition technology is a very popular topic in the fields of physiology, pattern recognition and computer vision, and related technologies are becoming more and more mature. In order to ensure the integrity of expression information, most studies are conducted under controlled experimental conditions. However, in practical applications, facial expression recognition needs to overcome various random problems such as illumination, occlusion, and posture. Therefore, facial expression recognition remains a challenging subject. In terms of occluded facial expression recognition, researchers have proposed many methods to reduce the impact of occlusion on expression recognition. The most commonly used methods in...

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Problems solved by technology

[0004] In order to overcome the shortcomings of the lack of robustness and poor classification effect of the classification method described in the above prior art, the present invention provides an occlusion expression recognition algorithm that combines double dictionaries and error matrices

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