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Satellite video target tracking method based on high-resolution twin network

A target tracking and high-resolution technology, which is applied in the field of satellite video target tracking, can solve the problems of large single-frame images of satellite video, few characteristic features, and high real-time requirements for tracking methods.

Active Publication Date: 2020-06-12
WUHAN UNIV
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AI Technical Summary

Problems solved by technology

[0005] (1) The single-frame image of satellite video is large, and the real-time performance requirements of the tracking method are very high
[0006] (2) The tracking target is small, the spatial resolution is low, and the characteristic features are few
[0008] (4) Motion blur, very similar to the background

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  • Satellite video target tracking method based on high-resolution twin network
  • Satellite video target tracking method based on high-resolution twin network
  • Satellite video target tracking method based on high-resolution twin network

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Embodiment Construction

[0041] In order to facilitate those skilled in the art to understand and implement the technical solution of the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. to limit the present invention.

[0042] The invention discloses a satellite video target tracking method based on a high-resolution twin network, figure 1The overall structure diagram of the tracking method is shown, which includes the tracking branch and the fine-tuning branch. The tracking branch, the basic framework is SiamRPN [1], which mainly includes the twin feature extraction sub-network and the twin region generation sub-network. The twin feature extraction sub-network uses a high-resolution parallel network [2], as shown in Figure 2(a). The network maintains high-resolution representations by connecting high-resolution to low-resolution convolutions in parallel, and repeatedly performs multi-scale fusion acros...

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Abstract

The invention discloses a satellite video target tracking method based on a high-resolution twin network. According to the method, a lightweight parallel network is adopted to obtain representation ofsmall target high resolution, and robust and real-time tracking is realized. A pixel-level fine adjustment model is provided on the basis of tracking. The method comprises the following steps: establishing a Gaussian mixture model by using inter-frame motion information, and detecting changed pixels to obtain a binary mask pattern; and repeatedly iterating on the mask pattern by adopting a MeanShift algorithm to achieve fine adjustment of a pixel level. Meanwhile, the complementarity of the surface features and the motion features is considered, adaptive fusion is further carried out on the tracking position and the fine adjustment position, and finally more accurate tracking is obtained.

Description

technical field [0001] The invention belongs to the technical field of satellite video target tracking, and in particular relates to a satellite video target tracking method based on a high-resolution twin network. Background technique [0002] Object tracking is an important branch of computer vision science. It has a wide range of applications in video surveillance, intelligent transportation, human-computer interaction, military field, and robot visual navigation. Its purpose is to realize target tracking and positioning through a certain similarity measure and matching search method. So far, the development of target tracking technology in traditional video sequences is relatively perfect. For different application scenarios and requirements, researchers have designed and developed a variety of target tracking methods. Recently, deep learning-based Siamese networks have attracted much attention in traditional tracking due to their amazing accuracy and speed. These Sia...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/246G06K9/62G06N3/04G06N3/08
CPCG06T7/246G06N3/08G06T2207/10016G06T2207/10032G06N3/045G06F18/253
Inventor 杜博邵佳武辰
Owner WUHAN UNIV
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