Human body behavior identification method based on principal component analysis

Abstract

A human body behavior identification method based on principal component analysis; the method comprises human body behavior modeling process and human body behavior identification process; the human body behavior modeling process comprises the following steps: obtaining a training dataset; using a filtering characteristic selection method to extract basic characteristic information; carrying out K-means algorithm clustering process for the extracted basic characteristic information dataset, and forming a human body behavior classifier; the human body behavior identification process comprises the following steps: building a BP nerve network model; importing human body behavior classification data into the nerve network, and using a quasi-Newton back-propagation method to train the data; using a BP nerve network algorithm to continuously improve and optimize the human body classifier; dispersing the output result, thus obtaining the human body behavior identification process result. The human body behavior identification method is simple and efficient, high in identification accuracy, wide in expansibility, stable and reliable in working performance, and wide in applications.

Description

technical field [0001] The present invention relates to the field of computer pattern recognition, and further designs the technical field of machine learning and human behavior analysis and intelligent understanding, specifically refers to a processing method for modeling and recognizing human behavior based on principal component analysis technology in a computer system, so that On this basis, the computer can automatically classify and identify different behaviors. Background technique [0002] The recognition and analysis of human behavior is a research hotspot in the field of modern computers, and its research is mainly devoted to finding technical methods to enable computers to intelligently learn and recognize human behavior and even complex human behavior. It is very important to recognize and understand human behavior in images acquired by cameras, but surveillance cameras also have shortcomings such as limited monitoring range and indoor monitoring that easily viol...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of existing human behavior recognition methods, such as complex modeling, low recognition accuracy, poor scalability, and poor applicability, the present invention provides a simple, efficient, high recognition accuracy, and better extension It is a human behavior recognition method based on principal component analysis that is stable and reliable in performance and performance and widely used.

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