Human body behavioral modeling identification method based on priori knowledge cluster in computer system

Abstract

The invention relates to a human body behavioral modeling identification method based on a priori knowledge cluster in a computer system. The method comprises the steps of human body behavioral modeling processing and human body behavioral identification processing. By the adoption of human body behavioral modeling identification method based on the priori knowledge cluster in the computer system, a constructed modeling system has a self-learning capacity and can continuously perfect a classifier along with the classification of observed samples. In cluster distribution obtained in the process of human body behavioral modeling, if outliers exist, the outliers serve as an abnormal behavioral model. When the system is designed, precaution is given as required, the method has great realistic meanings, important influence of priori knowledge on a human body behavioral identification result is considered, an improved cluster method is adopted to model and identify the human body, and foundation can be laid for identifying abnormal behaviors. The method is simple and efficient, can accurately identify different behavioral modes, and has good expandability. Working performance is reliable and stable, and the application range is wide.

Description

technical field [0001] The invention relates to the field of computer pattern recognition, in particular to the technical field of visual analysis and intelligent understanding of human behavior, and specifically refers to a method for modeling and recognizing human behavior based on prior knowledge clustering technology in a computer system. Background technique [0002] In recent years, domestic surveillance cameras have been installed in important locations in cities, which have provided important clues for the detection of many criminal cases. The recognition and understanding of human behavior in video images captured by a large number of cameras is particularly important. As the most active topic in the field of intelligent video surveillance, it has important practical significance and application value. [0003] As human behavior is a series of time-varying signals, the modeling and recognition of human behavior can be transformed into a classification problem of tim...

AI Technical Summary

Problems solved by technology

However, the established model is too complex, and there is a problem that the training time is too long

[0007] In summary, the current methods for modeling and recognition of human behavior are generally overly complex and computationally complex, and are often aimed at certain types of practical applications (such as abnormal behavior recognition), with weak scalability and no prior knowledge The impact on human behavior recognition results, and prior knowledge plays an important role in human behavior recognition

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