Method for removing dynamic background based on online transmission transformation and low-rank sparse matrix decomposition

Abstract

The invention discloses a method for removing a dynamic background based on online transmission transformation and low-rank sparse matrix decomposition, belonging to the field of video image background removal. The invention solves the problem that a foreground and a background in a moving video image sequence cannot be effectively separated in the prior art. The method comprises the following steps: carrying out graying preprocessing on a video sequence; carrying out feature point matching on two adjacent frames of images based on a Surf matching algorithm; after matching, calculating the Euclidean distance between feature matching points of two adjacent frames of images, determining the foreground speed and the background speed according to a clustering method, meanwhile, determining a projection operator, carrying out the motion process of a transmission transformation simulation camera according to the projection operator, and acquiring a processed video image sequence; performingonline low-rank sparse matrix decomposition based on the speed and the video image sequence, and correcting the foreground part after decomposing each image; and after correction, reconstructing an original video sequence according to transmission inverse transformation to obtain a foreground image sequence and a background image sequence. The method is used for dynamic background removal.

Description

technical field [0001] A method for removing dynamic background based on online transmission transformation and low-rank sparse matrix decomposition is used for dynamic background removal and belongs to the field of video image background removal. Background technique [0002] Low rank and sparse matrix decomposition (Low rank and sparse matrix decomposition) belongs to the technique of statistical modeling, that is, the subspace learning algorithm. Low-rank sparse matrix decomposition is one of the main technologies of current video background modeling. It is a method to separate moving objects from the background. Through a certain optimization process, the observation matrix composed of a group of observation frames can be accurately obtained. Low rank sparse representation. Among them, the low rank represents relevant parts in the video, i.e. background information, while the sparse representation contains outliers related to the background, i.e. moving objects. The lo...

AI Technical Summary

Problems solved by technology

[0005] In view of the problems of the above research, the purpose of the present invention is to provide a method based on online transmission transformation and low-rank sparse matrix decomposition to remove dynamic background, which solves the problem of low-rank sparse matrix decomposition in the prior art, which cannot convert the dynamic background in the sequence of moving video images. The problem of effective separation of foreground and background

Images