Face identification method based on low-rank decomposition and auxiliary dictionary under complex environment

Abstract

The invention discloses a face identification method based on low-rank decomposition and an auxiliary dictionary under complex environments; the method comprises the following steps: 1, using a non-salient robust principal component analysis method to make low-rank decomposition for an inputted face image, solving a target function based on a norm, and obtaining low-rank contents with complex environment influence primarily removed; 2, correlation-free low-rank decomposition based on a nuclear norm: adding regular terms with inter-class correlation removed into the target function, carrying out singular value decomposition for the low rank contents obtained by previous step for an initialization matrix, and using an ADMM algorithm alternative iteration to solve the low rank dictionary foridentification; 3, classification identification based on auxiliary dictionary learning: obtaining the auxiliary dictionary that simulates complex environment changes, simultaneously using the auxiliary dictionary with the low rank dictionary, and carrying out face classification identification via RADL. The method uses the low rank decomposition target function to fully remove interference information, thus enabling the decomposed face image to have more ID identification capability and anti-environment interference ability.

Description

technical field [0001] The invention belongs to the technical field of computer image processing, and relates to a face recognition method based on low-rank decomposition and an auxiliary dictionary in a complex environment. Background technique [0002] Face pictures always contain rich facial information. In recent years, the processing and research of face pictures have also covered all aspects of application life. In the fields of artificial intelligence, pattern recognition and image processing, face recognition occupies a place and is a research hotspot of classic algorithms and advanced technologies. At present, many face recognition research methods are carried out under good environmental conditions such as no occlusion or no illumination changes. In a real environment, we often have to process face pictures with changes in occlusion, noise, illumination, and expression. Therefore, the robustness and recognition rate of many face recognition techniques will decrea...

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Problems solved by technology

[0005] The purpose of the present invention is mainly aimed at the shortcomings of low face recognition accuracy, poor robustness, and slow recognit

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