Action Recognition Method Based on Deep Nonnegative Matrix Factorization Under Time-Dependent Constraints

Abstract

The invention discloses a behavior recognition method based on deep non-negative matrix decomposition under time-dependent constraints, which mainly solves the problems of insufficient expression of features extracted by existing methods and low behavior recognition rate. Its implementation steps: 1) extract the significant motion area of ​​the original video, and construct the corresponding non-negative matrix set in sections; 2) add time-dependent constraints, and construct time-dependent constrained non-negative matrix decomposition; 3) use time-dependent constrained non-negative matrices Decompose and construct a deep non-negative matrix decomposition framework under time-dependent constraints with a depth of L, and use this framework to decompose the data in the non-negative matrix set; 4) Normalize the coefficient matrices output by each layer and concatenate them as space-time Feature output; 5) Build a bag-of-words model for space-time features, and then identify and classify through the SVM classifier. The invention can obtain space-time features with high discriminative and expressive properties, and can be applied to occasions such as video surveillance and motion analysis that require high accuracy of behavior recognition.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a human behavior recognition method, which can be used for intelligent video monitoring and human-computer interaction. Background technique [0002] Human behavior recognition technology has broad application prospects and very considerable economic value, and the application fields involved mainly include: video surveillance, motion analysis, virtual reality, etc. Researchers have carried out a lot of in-depth research on the related technologies of human behavior recognition, and accumulated rich research results, but on the whole, the research field of human behavior recognition is still in the basic research stage, and there are still many key problems and problems. Technical difficulties need to be solved urgently, such as researching a relatively simple behavior representation method with high recognition rate and high robustness. Some scholars have found that the ...

AI Technical Summary

Problems solved by technology

However, when the basic non-negative matrix factorization method is applied to video feature extraction, only the spatial features of each frame of the video are considered, and the space-time features of the video are ignored.

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