Human body behavior identification method based on quantum neural network

A technology of quantum nerves and recognition methods, applied in the field of human behavior recognition, can solve problems such as inability to make full use of quantum parallel computing capabilities, inflexible processing, and poor recognition accuracy

Active Publication Date: 2020-08-25
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 body behavior identification method based on quantum neural network
  • Human body behavior identification method based on quantum neural network
  • Human body behavior identification method based on quantum neural network

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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

A human body behavior recognition method based on the quantum neural network comprises the steps: 1, collecting human body action images, and carrying out graying on each frame of image; 2, storing the human body action image in a quantum state to form an NEQR quantum image; 3, quantum image foreground detection: respectively detecting a static target and a moving target for the NEQR quantum imageby adopting a background difference method and a ViBe algorithm; 4, using a Hadamard door edge detection algorithm to extract edge information of human body actions from the 'moving object' in the step 3 to form an edge quantum image; 5, performing convolution operation on the 'edge quantum image ' in the step 4 based on a convolution method of a quantum black box to extract feature points of actions, and making an identification sample set; and 6, reading the trained weight, and constructing a quantum BP neural network to identify the identification sample set. The scheme has the advantagesthat 1) quantum image processing is more flexible, 2) the parallel computing capability of quantum is fully utilized, and 3) the quantum neural network improves the accuracy of human body 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 Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06N3/04G06N3/08G06N10/00
CPCG06N10/00G06N3/084G06V40/20G06V10/44G06N3/044
Inventor 常丽朱宇祥
Owner SHENYANG POLYTECHNIC UNIV
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