Training method and device of RGBT target tracking model

Abstract

The invention discloses a training method and device of a RGBT target tracking model, and the method comprises the steps: 1) building a tracking model which consists of a dense feature aggregation module and a classification module in sequence, and the dense feature aggregation module comprising a first convolution layer sequence for extracting the features of a visible light image; extracting a second convolution layer sequence of the thermal infrared image features, wherein the convolution layer with the same depth as the second convolution layer in the first convolution layer is a paired convolution layer; wherein the paired convolution layers except the first paired convolution layer correspond to one feature aggregation layer, and the convolution result of the first paired convolutionlayer is input into the feature aggregation layer of the next paired convolution layer; the classification module comprising a plurality of full connection layers which are sequentially connected inseries; and 2) training a tracking model by using the pre-marked visible light image sample and the pre-marked thermal infrared image sample to obtain a target tracking model. According to the method,a target identification result can be more accurate.

Description

technical field [0001] The present invention relates to a model training method and device, and more particularly to a training method and device for an RGBT target tracking model. Background technique [0002] Traditional target recognition is based on single modality, such as visible light. Visible light images contain rich geometric and texture details, but visible light images are sensitive to light, and the quality of information that images can convey in complex scenes will be greatly affected. Thermal infrared images reflect the distribution of surface temperature in the scene, so they are not sensitive to illumination changes, have good penetration and special ability to identify camouflage. Therefore, we can take advantage of the complementary characteristics of the two modalities, use RGBT (Red Green Blue Thermal, red, green, blue thermal infrared) tracking technology to fuse the features in the visible light image with the features in the infrared image, and use ...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a training method and device for

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