Remote video identity recognition system based on deep convolutional neural network
A neural network and remote video technology, applied in the field of remote video identification system based on deep convolutional neural network, can solve problems such as poor facial recognition rate, and achieve the goal of overcoming illumination differences, improving facial recognition rate, and highly reliable remote video identification. Effect
Pending Publication Date: 2022-02-11
STATE GRID INFORMATION & TELECOMM GRP +2
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[0002] Most of the existing face recognition systems need to obtain well-lit and clear facial images to work, and face recognition algorithms can be roughly divided into two categories: appearance-based methods and feature-based methods. The basic idea of the former is Convert the two-dimensional face input to another space, and then use statistical methods to analyze the face pattern, such as eigenface, fisherface and SVM methods, while the appearance-based method needs to be specially processed, in terms of illumination differences, facial expression changes and occlusion The recognition rate of the face under the interference of objects and the like is poor
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[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0016] see figure 1 , the present invention provides a technical solution: a remote video identification system based on a deep convolutional neural network, including a central processing unit, the input end of the central processing unit is electrically connected to the output end of the storage module, and the output end of the central processing unit is connected to the output end of the storage module. The input end of the storage module is electrically c...
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The invention relates to the technical field of community intelligent services, and discloses a remote video identity recognition system based on a deep convolutional neural network. The system comprises a central processing unit, the input end of the central processing unit is electrically connected with the output end of a storage module, and the output end of the central processing unit is electrically connected with the input end of the storage module. The output end of the central processing unit is electrically connected with the input end of the recognition module, the input end of the central processing unit is electrically connected with the output end of the recognition module, the input end of the central processing unit is electrically connected with the output end of the communication module, and the output end of the central processing unit is electrically connected with the input end of the communication module. According to the remote video identity recognition system based on the deep convolutional neural network, interference of illumination differences, facial expression changes, shelters and the like is overcome through the recognition module based on the convolutional neural network, the facial recognition rate is improved, and high-reliability remote video identity recognition is achieved.
Description
technical field [0001] The invention relates to the technical field of community intelligent services, in particular to a remote video identification system based on a deep convolutional neural network. Background technique [0002] Most of the existing face recognition systems need to obtain well-lit and clear facial images to work, and face recognition algorithms can be roughly divided into two categories: appearance-based methods and feature-based methods. The basic idea of the former is Convert the two-dimensional face input to another space, and then use statistical methods to analyze the face pattern, such as eigenface, fisherface and SVM methods, while the appearance-based method needs to be specially processed, in terms of illumination differences, facial expression changes and occlusion The recognition rate of the face under the interference of objects and the like is poor. Contents of the invention [0003] (1) Solved technical problems [0004] Aiming at the...
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IPC IPC(8): G06F21/32G06V40/16G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06F21/32G06N3/08G06N3/045G06F18/2415
Inventor 刘方宋奕冰冯英王刘旺姚影
Owner STATE GRID INFORMATION & TELECOMM GRP