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Tracking method of multiple feature points of microscopic sequence image

A sequential image, multi-feature technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as poor tracking effect and large 3D reconstruction error

Active Publication Date: 2011-02-16
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the disadvantages of large three-dimensional reconstruction error and poor tracking effect of the existing multi-feature point tracking method for microscopic sequence images, the present invention provides a multi-feature tracking method for microscopic sequence images that can effectively reduce three-dimensional reconstruction errors and improve the tracking effect. point tracking method

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  • Tracking method of multiple feature points of microscopic sequence image
  • Tracking method of multiple feature points of microscopic sequence image
  • Tracking method of multiple feature points of microscopic sequence image

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example

[0079] Example: For rigid multi-template T(X 0 (i) ) tracking, first initialize the rotation matrix R 0 and translation M 0 .M t is to move from the origin of the image to the current tracking point bt s position. Therefore, we define the number of origin coordinates matching the tracked point as Therefore define the translation vector of an equal number of tracking points, denoted as M 0 =(Mx 0 (1) ,My 0 (1) ,...,Mx 0 (i) ,My 0 (i) ) T , i=1,...,k, k=12, which is equal to b 0 =(274, 222, 271, 200, 237, 153, 214, 150, ...) T . In the results of multi-point tracking, the first 256 frames are more effective.

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Abstract

The invention provides a tracking method of multiple feature points of a microscopic sequence image, which comprises the following steps: 1) initializing a center coordinate of a tracking template of feature points as well as the size of a tracking window; 2) showing the status; 3) forecasting the status in an exponential function space described by Lie algebra; 4) calculating the distance between two covariance descriptors as the elements in a covariance value of a sample; 5) updating the status, figuring out a measurement function, and calculating posterior probability density at time t by a measuring value yt(i); and 6) estimating the optimum status, calculating weight and normalizing the weight by the posterior probability, judging whether to perform resampling, and outputting the estimated particles or ending multipoint tracking of the current frame; and repeating the steps, and finally completing multipoint tracking of the long-sequence microscopic image. The tracking method of the invention can help effectively reduce three-dimensional reconstruction errors and enhance tracking effect.

Description

technical field [0001] The invention relates to the fields of image processing, computer vision, calculation methods, feature tracking and the like, in particular to a multi-feature point tracking method for microscopic sequence images. Background technique [0002] In recent years, extensive research on feature point tracking has been driven by potential applications, such as the study of viruses and cells in the medical field, video surveillance systems, vehicle navigation systems, and human-computer interaction, etc. In the field of computer vision, it also plays a very important role such as 3D reconstruction, image segmentation, object recognition, etc. However, except for medical research, the research of feature point tracking in other microscopic fields is almost blank. It is well known that the acquisition of three-dimensional information and high-precision error detection of micro-components are very necessary. The tracking and matching of feature points can guid...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 刘盛方婷管秋陈胜勇王万良
Owner ZHEJIANG UNIV OF TECH
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