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Method for tracking anti-shield movement object based on average value wander

A mean shifting and moving target technology, applied in image data processing, instrumentation, computing, etc., can solve the problems of not considering the obvious change of target color, not applicable, not making full use of target moving direction and moving speed information, etc.

Inactive Publication Date: 2008-12-17
SHANGHAI JIAO TONG UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method does not consider the situation when the target color changes significantly or the surrounding environment interferes, and does not make full use of the target's movement direction and speed information in space, so this method often suffers from dynamic changes in the scene or occurrence of becomes inapplicable due to obscuration

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  • Method for tracking anti-shield movement object based on average value wander
  • Method for tracking anti-shield movement object based on average value wander
  • Method for tracking anti-shield movement object based on average value wander

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Embodiment Construction

[0053] The embodiments of the present invention are described in detail below in conjunction with the accompanying drawings: this embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following the described embodiment.

[0054] like figure 1 As shown, this embodiment implements the specific implementation process:

[0055] ① On the first frame of image, frame the tracking area. Each feature point in this area is used as the basis for the subsequent mean shift operation. In this step, the image information acquisition is completed, the first frame of image is read by using the OpenCv standard function library function cvQueryFrame, and the standard function bgr2hsv is called to convert the image RGB color space into a gray space, thereby establishing the pixel value matrix of the fir...

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Abstract

The invention relates to an anti-overlap method for tracking a moving target based on mean shift and belongs to the image processing technology field. The method comprises the following steps: constructing a mean shift model and a Kalman filter model; pre-estimating by utilizing a Kalman filter to obtain the initial position of searching each frame mean shift; obtaining the outline of an object by an image difference method; and defining whether similar factors can shade the object or not. When the similar factors shade the object, the position of the object in current frame is predicted and serves as a starting point for predicting the next frame by attaching different weights to color information and movement information respectively, according to the difference of mobile status of the object. Accordingly, the linear prediction of target position replaces the function of Kalman filter. Experiments prove that the method can realize the tracking of a quickly moving object and has good robustness for shading.

Description

technical field [0001] The invention relates to a moving target tracking method in the technical field of image processing, in particular to a mean shift-based anti-occlusion moving target tracking method. Background technique [0002] With the development of multimedia technology, people are exposed to more and more even massive video information. A large amount of video information is in motion scenes. Due to the strong correlation between adjacent frames in the video and the continuity of the temporal state of the moving object, it is possible to better detect, segment, identify and track the moving object. Moving object tracking is one of the most important applications in the field of computer vision, and has a wide range of applications in transportation, military, sports and other fields. [0003] Commonly used are the tracking method based on Mean Shift and the tracking method based on Kalman filter. But both methods have their disadvantages: [0004] The mean sh...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20
Inventor 梁静支琤
Owner SHANGHAI JIAO TONG UNIV
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