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Target tracking method based on compressive sensing theory and gcforest

A technology of target tracking and compressed sensing, which is applied in character and pattern recognition, instruments, calculations, etc., can solve problems such as large amount of computation, failure to apply, occlusion, deformation, and poor resolution of lighting problems, achieving reduced computation and high Effects of precision and robustness

Active Publication Date: 2021-04-30
BEIJING UNIV OF TECH
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Problems solved by technology

[0005] The shortcomings of the existing methods: on the one hand, the classic tracking algorithm is very good for the tracking of specific targets, and can achieve real-time performance, but it is not generalizable and cannot be applied to various occasions. , If the lighting problem is not solved well, it will easily lead to tracking failure; on the other hand, the tracking algorithm based on deep learning has greatly improved the tracking accuracy, and can basically reach an accuracy of more than 95%, but the algorithm structure is complex and the amount of calculation is high. Large, unable to meet real-time requirements

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  • Target tracking method based on compressive sensing theory and gcforest
  • Target tracking method based on compressive sensing theory and gcforest
  • Target tracking method based on compressive sensing theory and gcforest

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Embodiment Construction

[0026] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0027] Such as figure 1 As shown, the target tracking method based on compressed sensing theory and gcForest according to the present invention comprises the following steps:

[0028] S1: Select a large number of image sequences related to the target to be tracked to pre-train a gcForest network offline to extract target features;

[0029] The gcForest network first performs offline training, and the specific training process is as follows:

[0030] A typical gcForest network mainly consists of multi-particle scanning layers and cascad...

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Abstract

The invention discloses a target tracking method based on compressed sensing theory and gcForest, comprising the following steps: obtaining the initial frame video image of the tracking target; extracting positive and negative sample image slices and performing multi-scale transformation to obtain multidimensional vectors; extracting and tracking through the gcForest network The deep-level features of the target are obtained to obtain the deep-level expression of the target; the compressed sensing theory is used to reduce the dimensionality of its features, and the final feature expression is obtained and the classifier is trained; the next frame image samples n windows around the target position of the previous frame, Use the classifier trained in the previous frame to classify, and get the window with the largest classification score as the tracking target, and use this to update the classifier parameters. The invention effectively improves the accuracy of video target tracking, can stably track the target under complex conditions, and effectively improves the real-time performance of target tracking due to the reduction of calculation amount.

Description

technical field [0001] The invention relates to a video target tracking method, which integrates advanced technologies in many fields such as image processing, pattern recognition, artificial intelligence, automatic control and computer, and particularly relates to a target tracking algorithm based on compressed sensing theory and gcForest. Background technique [0002] Video object tracking technology is an important issue in the field of computer vision research, and it is widely used in video surveillance, video retrieval, transportation, automatic driving, etc. Video target tracking mainly solves the problem of selecting one or more specific targets in a video image sequence, and continuously finds the position of this target in each frame in this continuous video sequence, and provides a complete target area at the same time, so as to complete Tracking tasks. This technology involves many fields, including image processing, pattern recognition, probability statistics, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/46G06F18/2411G06F18/214
Inventor 刘芳杨安喆王洪娟黄光伟路丽霞王鑫
Owner BEIJING UNIV OF TECH
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