Face detection method and device

A face detection, the first face technology, applied in the field of face detection, can solve the problems of low accuracy, low efficiency, low efficiency of face area, etc., to achieve accurate detection and ensure the effect of detection efficiency

Inactive Publication Date: 2018-04-03
BEIJING EYECOOL TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0008] The embodiment of the present invention provides a face detection method to solve the problems of low efficiency and low accuracy of the face detection method in the prior art
[0009] An embodiment of the present invention provides a face detection device to solve the problems of low efficiency and low accuracy in detecting face regions by the face detection device in the prior art

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no. 1 example

[0028]On the one hand, the first embodiment of the present invention provides a face detection method. Among the plurality of convolutional neural networks in the first embodiment, the first to Nth convolutional neural networks are cascaded in descending order of the scale of the convolutional neural networks. Among them, the small-scale convolutional neural network mainly extracts and screens the face area; the medium-scale convolutional neural network further filters candidate windows and rejects a large number of redundant windows; the large-scale convolutional neural network detects more accurately And label the face area. Such as figure 1 Shown is a flow chart of the face detection method according to the first embodiment of the present invention. The face detection method of the first embodiment specifically includes the following steps:

[0029] Step S101: input the image to be detected into the first convolutional neural network, the first convolutional neural netwo...

no. 2 example

[0094] The second embodiment of the present invention provides a face detection method. Among the plurality of convolutional neural networks in the second embodiment, the Nth convolutional neural network is the largest convolutional neural network among all the convolutional neural networks. Among them, the small-scale convolutional neural network mainly extracts and screens the face area; the medium-scale convolutional neural network further filters candidate windows and rejects a large number of redundant windows; the large-scale convolutional neural network detects more accurately And label the face area. Such as Figure 5 Shown is a flow chart of the face detection method according to the second embodiment of the present invention. The face detection method of this second embodiment specifically comprises the following steps:

[0095] Step S201: input the image to be detected into the first convolutional neural network, the first convolutional neural network detects the...

no. 3 example

[0115] The invention also provides a human face detection device. Among the multiple convolutional neural networks used in the face detection device, the first to Nth convolutional neural networks are cascaded in descending order of the scale of the convolutional neural networks. Among them, the small-scale convolutional neural network mainly extracts and screens the face area; the medium-scale convolutional neural network further filters candidate windows and rejects a large number of redundant windows; the large-scale convolutional neural network detects more accurately And label the face area. Such as Image 6 Shown is a structural block diagram of the face detection device according to the third embodiment of the present invention. The face detection device of the third embodiment specifically includes the following modules:

[0116] The first human face candidate window labeling module 301 is used to input the image to be detected into the first convolutional neural ne...

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Abstract

The invention provides a face detection method and device, and the method comprises the steps: inputting a to-be-detected image into a first convolution neural network, detecting a face region in theto-be-detected image through the first convolution neural network, and marking a first face candidate window in the detected face region; adjusting the scale of an (M-1) face candidate window to be the scale of an M-th convolution neural network, inputting the scale of the M-th convolution neural network into the M-th convolution neural network, detecting a face region of the (M-1) face candidatewindow through the M-th convolution neural network, and carrying out the marking of an M-th face candidate window in the detected face region, wherein M=2, 3, ..., N, and N >=3; merging an N-th face candidate window and an (N-1)-th face candidate window into a face well-chosen window through a global non-maximum suppression method, wherein the first convolution neural network, the second convolution neural network, ..., the N-th convolution neural network are cascaded according to a scale sequence of convolution neural networks from the small to the big. The invention also provides a face detection method and device. The method and device can detect the face region precisely and efficiently.

Description

technical field [0001] The invention relates to the technical field of face detection, in particular to a face detection method and device. Background technique [0002] With the rapid development of artificial intelligence and information technology, problems such as human-computer interaction and information security reflect the importance of computer vision. Using the interaction between computers and users to simulate the "communication" between people has become a key problem that needs to be solved urgently in the development of technology. Face detection is one of the basic techniques and a key step in many face analysis problems in human-computer interaction. [0003] Face detection is to use a detection algorithm to determine whether a given image contains a human face, and if so, to determine the position, size, and posture of the human face in the image. Compared with other biometric detection technologies, it is friendly and convenient. The application of face...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/02
CPCG06N3/02G06V40/161G06V40/172
Inventor 宋丽段旭张祥德
Owner BEIJING EYECOOL TECH CO LTD
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