Real-time space target feature point tracking method suitable for space tethered robot

A space tether and space target technology, applied in the field of pattern recognition, can solve the problems of low detection accuracy, long detection time of SIFT algorithm, lack of adaptive update strategy of feature points, etc., to achieve high matching accuracy, easy implementation and application, The effect of high target positioning accuracy

Inactive Publication Date: 2013-06-12
NORTHWESTERN POLYTECHNICAL UNIV
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AI Technical Summary

Problems solved by technology

[0008] For the tracking problem of space targets, the KLT algorithm mentioned above has the problem of low detection accuracy of feature points, inaccurate tracking caused by poor matc

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  • Real-time space target feature point tracking method suitable for space tethered robot
  • Real-time space target feature point tracking method suitable for space tethered robot
  • Real-time space target feature point tracking method suitable for space tethered robot

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Embodiment Construction

[0038] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0039] The embodiment of the present invention consists of five parts: feature point extraction algorithm, feature point matching algorithm, discrete point elimination, precise positioning and self-adaptive strategy. The overall flow chart is as follows figure 1 shown.

[0040] The hardware configuration required by the method of the present invention can be configured by a general household computer, and on the hardware of this configuration level, the method is realized by programming in C++ language. The key steps involved in the method of the present invention are described in detail one by one below, and the basic steps in the method of the present invention are the same, and the specific forms are as follows:

[0041] first step:

[0042] Video first frame image I 1 The target T to be tracked is marked with a rectangular area, and the four vertices are r...

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Abstract

The invention relates to a real-time space target feature point tracking method suitable for a space tethered robot. The method is mainly formed by a feature point extraction algorithm, a feature point matching algorithm, discrete point elimination, accurate positioning and a self-adaptive strategy. Feature points extracted through an improved SURF algorithm are strong in robustness and stability. The method enables the feature point matching accuracy and target positioning accuracy to be high, and is suitable for stable tracking of targets which have rapid changes in positions and gestures and are simple in structure in a multi-scale image sequence. The method has robustness in various types challenging situations, and the tracking process has short-term anti-occlusion capacity. The method can be used for achieving the real-time detection and tracking of a plurality of types of targets, is suitable for real-time robustness tracking for the space targets which have rapid changes in positions and gestures and are simple in structure in the multi-scale image sequence.

Description

technical field [0001] The invention belongs to the field of pattern recognition, relates to technologies such as image processing and computer vision, and relates to a real-time space object feature point tracking method suitable for a space tether robot. Background technique [0002] Due to the characteristics of low cost, passive detection, and strong robustness, visual sensors have received more and more attention in the tracking of moving targets. For example, space tethered robots use binocular vision to track space targets, missiles and other aircraft use vision Sensors track aerial targets, etc. [0003] However, the tracking of spatial objects in video sequences is a very complex task, and there are many challenges, such as the sequence contains object rotation, scale change, motion blur, and other related objects. Moreover, spatial objects usually have the following characteristics: simple structure and texture features, single grayscale features, large scale chan...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 黄攀峰蔡佳孟中杰刘正雄
Owner NORTHWESTERN POLYTECHNICAL UNIV
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