A face occlusion detection method based on cascaded convolutional neural network

Abstract

A face occlusion detection method based on a cascaded convolutional neural network, comprising the following steps: 1) acquiring a video frame image; 2) normalizing the image, and duplicating and saving two copies; 3) image 1 is grayscaled 4) Use a three-level cascaded network to perform head detection in the form of a multi-scale sliding window, and save the window coordinates and sizes that meet the conditions; 5) Perform cluster analysis on the window coordinates , to obtain the orientation of the target window; 6) According to the obtained data, the head area is intercepted in image 2, and normalized processing and brightness adjustment are performed; 7) The sub-regions are divided into two-level eye / mouth cascade networks in the form of multi-scale sliding windows. Eyes and mouth detection, if they do not meet the set conditions, it will be judged that the eyes / mouth are blocked and an alarm will be triggered. The invention has strong robustness to illumination and posture, adapts to various types of occluders, and has high detection accuracy.

Description

technical field [0001] The present invention relates to neural network, computer vision, image processing, pattern recognition and other technical fields, especially a method for processing, analyzing and understanding video signals, controlling a monitoring system, and realizing face occlusion detection. The method can be used In public places such as schools, banks, prisons, factories, etc., it is also applicable to the access control and surrounding areas of private houses. Background technique [0002] Biometric identification technology is a technology that uses automated technology to detect personal physiological characteristics or personal behavior characteristics for identity verification. It has been widely used in the fields of business, military, and criminal investigation. Among the many biometric features, face recognition technology has important academic research value and broad application prospects due to its advantages of initiative, non-invasiveness, user...

AI Technical Summary

Problems solved by technology

As the proportion of people wearing glasses in daily life increases, the problems caused by glasses blocking are becoming more and more common; environmental pollution has caused more and more common wearing masks when going out; in practical applications, such as smart access control, video Surveillance, security systems, criminal identification, etc., basically collect face images in a non-cooperative environment, which is easily blocked by other people or objects

[0003] These interference factors that cause occlusion make the face data acquired by the imaging device incomplete, causing the loss of part or even all of the face information, resulting in the inability of the face recognition system to extract complete and effective face information, which affects the entire face authentication system. The accuracy of detection and identification

Due to the variety of occlusion types, random positions, and uncertain sizes, there is no suitable method to model occlusion, which makes it very difficult to deal with occlusion problems

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