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Method and device of face detection

A face position and face recognition technology, applied in the field of face recognition, can solve problems affecting the accuracy of face recognition and loss of intermediate information, and achieve the effect of accurate description and accurate position determination

Inactive Publication Date: 2017-12-12
深图(厦门)科技有限公司
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Problems solved by technology

[0004] Based on this, it is necessary to provide a method and device for face recognition that can accurately recognize faces in view of the serious loss of intermediate information in the above-mentioned face recognition process that affects the accuracy of final face recognition

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  • Method and device of face detection

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Embodiment Construction

[0052] In order to make the object, technical solution and advantages of the present invention more clear, the specific implementation manners of the face detection method and device of the embodiment of the present invention will be described below with reference to the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0053] like figure 1 Shown, in the method for the face recognition of wherein one embodiment, comprise the following steps:

[0054] S100. Acquire a target image for face recognition.

[0055] When performing face recognition in this method, it is generally implemented by a computer program. First, an image to be recognized is input, and after the image information is obtained, the face recognition program is formally started.

[0056] S200, performing multi-layer convolution processing on the target image. This step is to perform m...

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Abstract

The invention relates to a method and a device of face recognition. The method comprises the following steps: acquiring a target image on which face recognition needs to be carried out; carrying out multi-layer convolution processing on the target image; combining a preset number of pooling results of convolution feature mapping in a multi-layer convolution processing to obtain a final external processed image; classifying the final external processed image; carrying out bbox regression processing on the final external processed image; and calculating and obtaining a face position of the target image according to a classification processing result and a bbox regression processing result. Multi-layer convolution processing is carried out on the initial target image, and image features after convolution processing of different levels are combined to obtain the final external processed image. The last final external processed image generated by the method contains image detail information after intermediate convolution processing, multi-scale feature fusion is formed, description for the original target image is more accurate, and thus face recognition and position determination are also more accurate.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a face recognition method and device. Background technique [0002] In face image detection, the deep learning framework of Faster RCNN can be used, which is the most advanced deep learning scheme for general object detection. This scheme basically consists of two parts: (1) a Region Proposal Network (RPN) to generate a list of proposals for regions (or called Regions of Interest (RoIs)) that may contain objects; and (2) a region proposal network (RPN) for A Fast RCNN network that classifies image regions as objects (and background) and refines the boundaries of these regions. [0003] The usual face image detection includes several steps: acquire the image --- perform multi-level convolution processing --- use the preset algorithm to obtain the third external image according to the final convolution processing result, and finally calculate the face according to the th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V40/16G06V40/172G06N3/045G06F18/253
Inventor 孙旭东吴鹏程许主洪
Owner 深图(厦门)科技有限公司
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