Effective modeling and identification method of moving object behaviors

Abstract

The invention provides an effective modeling and identification method of moving object behaviors, which comprises the following steps: step 1, firstly extracting local features and then extracting moving features of the moving object behaviors by using a feature extraction module; step 2, fusing the extracted local features and the moving features by using a feature fusion module via a subspace learning method, and reducing dimensions on feature space by using the feature fusion module; and step 3, by combining a prototype learning algorithm with a measure learning algorithm, identifying themoving object behaviors by using a behavior identification module, and evaluating the identified moving object behaviors by using the behavior identification module. In the effective modeling and identification method, the local features and the moving features are subject to feature fusion treatment, thus reducing the dimensionality of the feature space, and improving robustness of feature expression. The effective modeling and identification method has the advantages of low storage and low computational complexity, and has preferable classification and identification performance. The effective modeling and identification method can be used for intelligently monitoring abnormal behaviors in public security fields, thus an alarm is given once the abnormal behavior is found.

Description

technical field [0001] The invention relates to the field of computer application technology, in particular to a method for modeling and identifying the behavior of a moving target. Background technique [0002] In recent years, surveillance cameras have been installed in important locations in cities in China. In many criminal cases, video surveillance videos have provided very important clues to solve the case. But most of the cameras installed in public places can only record the scene at that time, as the basis for investigation after the event, but can not achieve real-time automatic alarm. The modeling and recognition of moving target behavior can meet the urgent needs of automatic real-time alarm in intelligent monitoring. [0003] In recent years, due to the needs of public safety, the demand for intelligent monitoring has increased rapidly. In 1997, the U.S. Defense Advanced Research Projects Agency established a major visual surveillance project VSAM (visual surv...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the technical problem that the existing technical solutions can only record the scene at that time, but cannot achieve real-time automatic alarm, the purpose of the prese

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