Abnormal double-person interaction behavior recognition method based on vision co-occurrence matrix sequence

Abstract

The invention discloses an abnormal double-person interaction behavior recognition method based on a vision co-occurrence matrix sequence, and the method comprises the steps: 1, carrying out the motion detection and segmentation of a transaction behavior in a video collected by a camera; 2, respectively carrying out the regional HOG feature extraction of left and right action performers in the video; 3, constructing a vision word through employing the HOG features extracted at step 2 and a K-means algorithm, generating a vision word bag, coding the words in the vision word bag, carrying out the vision word coding of region features through employing a similarity measuring function, carrying out the statistics of vision co-occurrence relation among the interaction individuals in a time dimension, and obtaining the vision co-occurrence matrix sequence so as to represent the abnormal double-person interaction behaviors in the video; 4, carrying out the training and recognition of an HMM algorithm. The method is simple and efficient, and is higher in recognition accuracy. Aiming at the recognition of abnormal double-person interaction behaviors in an intelligent monitoring system, the method is better in recognition performances.

Description

technical field [0001] The invention belongs to the field of computer vision, and in particular relates to an abnormal two-person interactive behavior recognition method based on a visual co-occurrence matrix sequence. Background technique [0002] In the context of the era of big data, the field of computer vision has attracted much attention. Among them, the research on the recognition algorithm of abnormal human interaction behavior has become a hot issue. Computers with the ability to recognize interactive behavior can replace humans to efficiently and accurately complete tedious and important tasks; therefore , the research on the identification algorithm of abnormal interactive behavior has high practical value, and its results have broad application prospects in identifying abnormal two-person interactive behavior in intelligent monitoring systems. [0003] At present, there are generally two frameworks for abnormal two-person interaction recognition methods. One is b...

AI Technical Summary

Problems solved by technology

[0007] In order to solve the technical problems of low recognition rate and high computational complexity in the research on the above-mentioned abnormal two-person interaction recognition, the present invention effectively combines the advantages of the recognition method based on the symbiotic atomic action description and the probability graph model, and designs a visual symbiosis matrix based on Recognition Method of Sequential Abnormal Two-person Interaction Behavior

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