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Multi-feature-fused adaptive moving target tracking method

A moving target and adaptive technology, applied in the field of visual moving target tracking, can solve the problems of poor tracking accuracy and robustness, and achieve the effect of improving accuracy and robustness

Pending Publication Date: 2020-08-14
KUNMING UNIV OF SCI & TECH
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  • Abstract
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Problems solved by technology

[0005] The purpose of the present invention is to provide a multi-feature fusion adaptive moving target tracking method to solve the problem of poor tracking accuracy and robustness using only a single image feature in a complex environment

Method used

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  • Multi-feature-fused adaptive moving target tracking method
  • Multi-feature-fused adaptive moving target tracking method
  • Multi-feature-fused adaptive moving target tracking method

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Embodiment 1

[0041] Such as figure 1 As shown, the multi-feature fusion adaptive moving target tracking method provided in this embodiment includes the following steps:

[0042] (1) Obtain the initial position information of the target, that is, the position of the target in the first frame of the video, including the coordinates (x, y) of the upper left corner of the target frame, width and height.

[0043] (2) Extract the HOG features and convolutional features of candidate target samples according to the initial position information obtained in step (1). Specifically, the HOG features and convolutional features are respectively as figure 2 and image 3 As shown, the convolution features are extracted using the Conv3-4, Conv4-4 and Conv5-4 layers of the pre-trained convolutional neural network VGG19.

[0044] (3) According to the HOG feature and convolution feature extracted in step (2), the correlation filters are trained respectively, and then the response maps under different feat...

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Abstract

The invention relates to a multi-feature-fused adaptive moving target tracking method, and belongs to the field of visual moving target tracking. The method comprises: firstly, extracting HOG (Histogram of Oriented Gradient) features from an image target area, simultaneously extracting convolution features by utilizing a pre-trained convolution neural network, and then fusing the HOG features andthe convolution features by adopting a self-adaptive mode; and estimating a target position based on the fused feature response graph, solving a target scale change problem by adopting a scale estimation method, and finally performing model updating by adopting a sparse model updating strategy. The method can effectively solve the problems that only a single image feature is used for tracking in acomplex environment, and the precision and robustness are poor.

Description

technical field [0001] The invention belongs to the field of visual moving target tracking, and in particular relates to a multi-feature fusion adaptive moving target tracking method. Background technique [0002] In the field of computer vision, target tracking has always been an important topic, including statistics, image processing, machine learning, deep learning, signal processing and other related knowledge. Target tracking technology has broad application prospects in both military and civilian applications, mainly including human-computer interaction, military guidance, video surveillance, intelligent transportation, etc. Although great breakthroughs have been made in the object tracking problem in recent years, due to the complexity and diversity of the tracking environment, such as scale changes, illumination changes, object occlusion and other factors, achieving robust object tracking is still a very challenging problem. [0003] Target tracking methods can be d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/246G06K9/62
CPCG06T7/246G06F18/253
Inventor 尚振宏谢柳
Owner KUNMING UNIV OF SCI & TECH
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