Human behavior recognition method based on quantum neural network

A technology of quantum nerves and recognition methods, which is applied in the field of human behavior recognition, can solve the problems of inflexible processing, poor recognition accuracy, and inability to make full use of quantum parallel computing capabilities, and achieve improved accuracy and flexible quantum image processing. Effect

Active Publication Date: 2022-02-15
SHENYANG POLYTECHNIC UNIV
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AI Technical Summary

Problems solved by technology

[0003] Many current identification methods have the problems of inflexible processing, inability to make full use of quantum parallel computing capabilities, and poor identification accuracy.

Method used

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  • Human behavior recognition method based on quantum neural network
  • Human behavior recognition method based on quantum neural network
  • Human behavior recognition method based on quantum neural network

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Experimental program
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Embodiment Construction

[0135] 1. Transform traditional images into quantum images

[0136] The camera captures the video in the classic field and performs grayscale processing on each frame of the image, and the operation process uses the method of formula (1).

[0137] Gray(Y,X)=0.299*R(Y,X)+0.587*G(Y,X)+0.114*B(Y,X) (1)

[0138] Among them, Gray(Y,X) is the gray value of the position (Y,X), and R(Y,X), G(Y,X), and B(Y,X) are the three types of positions at (Y,X) respectively. Color value, * represents the multiplication sign. Then the NEQR model is used to store the human body action image in the quantum state. In a traditional grayscale image, each pixel is composed of grayscale value and position information, and the grayscale value is divided into 256 levels, from 0 to 255. NEQR uses two qubit binary strings to store the position information and grayscale information of image pixels respectively, and simultaneously entangles and superimposes the two, so that all pixels of the image can be st...

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Abstract

Human action recognition method based on quantum neural network, 1: collect human action images, and grayscale each frame of image; 2: use human action images to store in the quantum state to form NEQR quantum images; 3: Quantum image foreground detection: For the NEQR quantum image, the background difference method and the ViBe algorithm are used to detect the static target and the moving target respectively; 4: Use the Hadamard gate edge detection algorithm to extract the edge information of the human body movement from the "moving target" in the third step to form an edge quantum image; 5: The convolution method based on the quantum black box performs a convolution operation on the "edge quantum image" in the fourth step to extract the feature points of the action and make a recognition sample set; 6: Read the trained weights and build a quantum BP neural network The network recognizes the recognition sample set. This solution has the following advantages: 1) making quantum image processing more flexible; 2) making full use of quantum parallel computing capabilities; 3) quantum neural network improving the accuracy of human behavior recognition.

Description

technical field [0001] The solution of the invention is mainly used in the field of human behavior recognition. Background technique [0002] The main task of human behavior recognition research is to process and analyze the original image sequence, learn and understand human behavior. It comprehensively uses computer vision, image graphics, pattern recognition and artificial intelligence and many other knowledge and technologies to extract human moving objects from continuous video sequences, and at the same time continuously recognize and track the extracted moving objects, and The ultimate goal of understanding and describing human behavior is to identify human behavior. Quantum computing is currently the most mature and is generally considered to be the most likely new computing model to replace classical computing. In the past thirty years of development and research, through in-depth research on the properties of quantum superposition state, quantum entanglement stat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V40/20G06V10/44G06N3/04G06N3/08G06N10/00
CPCG06N10/00G06N3/084G06V40/20G06V10/44G06N3/044
Inventor 常丽朱宇祥
Owner SHENYANG POLYTECHNIC UNIV
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