A fast face detection method based on deep cascade convolutional neural network

Abstract

The invention discloses a fast face detection method based on a deep cascade convolutional neural network. The method includes creating a face data set, constructing a deep cascade convolutional neural network, testing the network model, using positive and negative samples to compose training set and verification set to train the depth cascade convolution neural network for deep learning, adding gender classification auxiliary task in the depth learning process, and adopting fine-tuning training at the same time. At the same time, the training method and network structure are optimized. The invention is based on a deep cascade convolutional neural network, the convolution layer is optimized to increase the network depth, and at the same time, the on-line difficult-to-negative sample miningmethod in the phase of auxiliary task training and fine-tuning training is introduced, which improves the classification accuracy of the network, reduces the false detection rate, and guarantees thedetection speed and accuracy of the method in practical application.

Description

technical field [0001] The invention relates to the field of face detection, in particular to a fast face detection method based on a deep cascaded convolutional neural network. Background technique [0002] Face detection plays an important role in face image analysis and is a fundamental problem in computer vision. Various face-based practical applications, especially in uncontrolled environments where face angles, scales, backgrounds, and exposures vary greatly, rely on accurate and fast face detection. [0003] As convolutional neural networks (CNNs) have made remarkable progress in computer vision tasks such as image classification and object detection, in the field of images, deep learning methods based on CNNs are more effective than traditional methods in solving various vision problems. Significant improvement has been made. [0004] The biggest difference between the deep learning method and the traditional method is that the features it uses are learned from mas...

AI Technical Summary

Problems solved by technology

[0006] In view of the above shortcomings, the present invention provides a fast face detection method based on a deep cascaded convolutional neural network to solve the problems of high hardware cost and slow detection speed when the existing method is integrated, and has high detection accuracy and robust performance Good, simple network structure, etc.

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