Complex scene-oriented multi-source target tracking method

Abstract

The invention relates to the technical field of artificial intelligence, and provides a complex scene-oriented multi-source target tracking method, which comprises the following steps: forming an initial deep learning network, setting a weight of the initial deep learning network, and performing steepest gradient dimensionality reduction on the weight of the initial deep learning network to obtainan initial feature matrix of a multi-source target; performing simplified sparse representation and sparse processing on the initial feature matrix of the multi-source target to obtain a sparse target feature matrix; and classifying the sparse target feature matrixes, and establishing feature matrix representations for forming different feature targets. The multi-source target feature matrix library established through the deep learning network has good modeling characteristics and a data statistical structure, and a multi-source target tracker model can be generated for label-free training data.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a multi-source object tracking method for complex scenes based on deep learning. Background technique [0002] The multi-source target tracking method for complex scenes can provide accurate target data features, and realize the tracking of multi-source targets by constructing a deep learning processing architecture based on feature matrix learning. Specifically, a template is formed by training feature matrices of a large number of typical simulation scenarios, and an autonomously controllable and addable template model is obtained. This model also has the feature matrix enhancement function of the scene, which can realize the enhancement of special features such as shadows and textures of the scene. [0003] As a signal transformation method, feature matrix learning can approximate high-dimensional spatial features with low-dimensional spatial vectors based on complete...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiment of the present invention is to provide a complex scene-oriented multi-source target tracking method based on deep learning, aiming at solving the technical problems that the existing technology is difficult to reduce the dimension of the feature matrix and cannot more closely represent the real target

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