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Method for tracing covariance matrix based on grayscale restraint

A covariance matrix and grayscale technology, applied in the field of image detection, can solve the problems of inability to obtain tracking results, weak feature description, etc., and achieve the effect of reducing the amount of calculation, high accuracy, and accurate target positioning.

Inactive Publication Date: 2010-02-17
TIANJIN UNIV
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AI Technical Summary

Problems solved by technology

However, since the feature description of the target by the kernel function histogram in the Mean shift method is relatively weak, it is impossible to achieve ideal tracking when tracking the target on a grayscale image or an image with less texture information, especially when the color of the target and the background are similar. result

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  • Method for tracing covariance matrix based on grayscale restraint
  • Method for tracing covariance matrix based on grayscale restraint
  • Method for tracing covariance matrix based on grayscale restraint

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Embodiment Construction

[0020] The invention adds a gray scale constraint method on the basis of covariance matrix tracking to each frame image in the video sequence. Specifically, the present invention uses a covariance matrix to describe the tracking target, and utilizes grayscale constraints to filter out candidate targets, and then uses the difference value of the covariance matrix to judge the matching degree between the candidate target and the tracking target, and finally compares the tracking target according to the matching degree. Track the target for positioning.

[0021] The present invention is a covariance matrix tracking method based on gray scale constraints, figure 1 It is an overall flow chart, specifically including the following steps:

[0022] 1. Select the tracking target

[0023] Such as figure 2 Select a target in the image as shown. figure 2 The rectangle area with solid line in the middle is the initial position of the selected tracked target, the length is M pixels, a...

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Abstract

The invention belongs to the technical field of image detection and relates to a method for tracing a covariance matrix based on grayscale restraint, which comprises the following steps: selecting a rectangular area of a image as a target model to trace; calculating a grayscale value of each point of the target model; extracting the characteristic vector of each point of the target model; calculating the covariance matrix of the target model; after the length and the width of a subsequent frame are respectively amplified by taking the target model as a center, obtaining a tracing window, selecting a candidate target and checking whether the candidate target meets the grayscale restraint or not; and calculating a difference value of the covariance matrix of the candidate target which meetsthe grayscale restraint and the target model, wherein the candidate target area with the minimal difference value is the position of a traced target. The invention has the advantages of more accuratetarget positioning, higher tracing speed and higher instantaneity.

Description

technical field [0001] The invention belongs to the technical field of image detection and relates to a moving target tracking method which can be used for real-time video monitoring. Background technique [0002] The background technology involved in the present invention has: [0003] (1) Covariance matrix tracking algorithm (see literature [1]): The covariance matrix tracking algorithm finds the characteristics of the target area frame by frame from the input video sequence, and uses the covariance matrix to model the target features, and then according to the covariance matrix to find the best feature-matching region. This method achieves the fusion of multiple features of the target very well, and has strong adaptability to rotation, scaling and brightness changes. [0004] (2) Mean shift algorithm (see literature [2]): Mean shift algorithm is a non-parametric probability density estimation algorithm, which generally uses a histogram to model the target, and then meas...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 操晓春邓超张炜王秀锦李雪威
Owner TIANJIN UNIV
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