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Method for accurately tracking characteristic points of quick movement target

A fast motion, feature point technology, applied in image data processing, instruments, calculations, etc., can solve the problems of feature point tracking loss, discontinuous brightness change, etc., to improve the search time and save the search time.

Inactive Publication Date: 2010-12-22
CHINA DIGITAL VIDEO BEIJING
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  • Description
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Problems solved by technology

[0003] However, when using the existing KLT optical flow feature point tracking algorithm to track fast targets, it is easy to lose feature point tracking due to discontinuous brightness changes

Method used

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  • Method for accurately tracking characteristic points of quick movement target
  • Method for accurately tracking characteristic points of quick movement target
  • Method for accurately tracking characteristic points of quick movement target

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Embodiment Construction

[0022] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0023] The method for accurately tracking the feature points of the fast moving target provided by the present invention involves the determination of two areas, one is to select a rectangular area for the tracking target to determine in which range of the image to generate the feature points, and the tracking target selects the rectangular area as the user Selected, such as a face area; the other is the tracking target search rectangular area to determine in which range to pre-search for missing feature points, and the tracking target search rectangular area is generally the entire image area. The specific process of this method is as follows figure 1 shown, including the following steps:

[0024] (1) At time t-1, in the tracking target selection rectangular area, according to the feature matrix Select M feature points. g x Indicates th...

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Abstract

The invention belongs to video and image processing technology and particularly relates to a method for accurately tracking characteristic points of a quick movement target. The method comprises the following steps of: selecting M characteristic points in a tracked target selection rectangular region at the moment of t-1 according to characteristic matrixes; iterating the M characteristic points at the moment of t by using a KLT luminous flux vector formula to solve the optimal solution so as to acquire the new positions of the current frames of all the characteristic points; and estimating the proximity positions of all the characteristic points by using a checker in a tracked target searching rectangular region if the optimal solution cannot be solved so as to acquire new positions. Due to the adoption of the method, the proximity positions can be found, then the optimal position can be solved by the luminous flux vector calculation formula, and a search region is partitioned by using the checker, so that search time is saved greatly, and the proximity positions with approximate gray scale variation to that of the tracked target can be searched. The method avoids the situation of losing the tracking of the characteristic points and is very suitable for tracking the characteristic points of the quick movement target.

Description

technical field [0001] The invention belongs to video and image processing technology, in particular to a method for accurately tracking feature points of a fast moving target. Background technique [0002] In the image / video post-processing software, the pixel feature area of ​​the moving image is tracked, and the tracking data can be used to control the movement of other objects and stabilize the moving object, which has a wide demand. The KLT optical flow feature point tracking method can be used to track the feature points. The KLT optical flow feature point tracking algorithm usually selects a set of feature points in the reference frame, assuming that the texture of the feature points remains unchanged between frames, and then completes it through local matching search. Track tasks. The Kanade-Lucas-Tomasi (KLT) algorithm uses the sum of squares (SSD) of image gray level differences as the matching criterion of feature points. For the specific KLT feature point track...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 见良郑鹏程刘铁华孙季川
Owner CHINA DIGITAL VIDEO BEIJING
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