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Single-emission multi-frame infrared target detection method

A technology of infrared target and detection method, which is used in instruments, biological neural network models, character and pattern recognition, etc.

Pending Publication Date: 2020-10-30
HENAN UNIV OF SCI & TECH
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Problems solved by technology

[0004] In view of this, in order to solve the above-mentioned deficiencies in the prior art, the object of the present invention is to provide a single-shot multi-frame infrared target detection method, which integrates multi-scale feature weighted fusion and scale-invariant positioning loss, and has the ability of self-learning and detection It is an effective way to solve the problem of infrared imaging guidance target detection in complex environments.

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  • Single-emission multi-frame infrared target detection method
  • Single-emission multi-frame infrared target detection method
  • Single-emission multi-frame infrared target detection method

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Embodiment Construction

[0032] Specific examples are given below to further describe the technical solution of the present invention in a clear, complete and detailed manner. This embodiment is the best embodiment on the premise of the technical solution of the present invention, but the protection scope of the present invention is not limited to the following embodiments.

[0033] A single-shot multi-frame infrared target detection method, comprising the following steps:

[0034] S1: Starting from the feature pyramid network, based on learnable weights to describe the inequality of the contribution of each feature layer to the fusion output, realize the two-way multiplexing between the low-resolution, strong semantic feature layer and the high-resolution, weak semantic feature layer Weighted fusion of scale features to build an auxiliary network;

[0035] S2: Starting from the intersection and union ratio, while considering the influence of overlapping and non-overlapping areas on the objective fun...

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Abstract

The invention relates to a single-transmission multi-frame infrared target detection method, which comprises the following steps of: starting from a feature pyramid network, describing the inequalityof contribution of each feature layer to fusion output on the basis of learnable weights, achieving bidirectional multi-scale feature weighted fusion between a low-resolution and strong-semantic feature layer and a high-resolution and weak-semantic feature layer, and constructing an auxiliary network; based on the cross-parallel ratio, considering the influence of an overlapping region and a non-overlapping region on a target function at the same time, constructing detector positioning loss keeping invariance to target scale change, constructing a target detector, and improving the sensitivityof a detection model to small target positioning errors. A VGG16 convolutional neural network is used as a feature extraction network and is integrated with an auxiliary network and a target detectorto form a single-shot multi-frame infrared target detection model fusing multi-scale feature weighted fusion and scale invariance positioning loss. The method has autonomous learning ability and highdetection rate, and is an effective way for solving the infrared imaging guidance target detection problem in a complex environment.

Description

technical field [0001] The invention belongs to the technical field of infrared target detection, and in particular relates to a single-shot multi-frame infrared target detection method. Background technique [0002] At present, target detection is the basis for the automatic target recognition system of infrared imaging guidance to complete subsequent tasks such as recognition and tracking. The existing system does not have the ability to learn target characteristics independently, and once the task environment exceeds the pre-planned conditions, it will be powerless. The single-stage target detection based on deep learning has self-learning ability and high computational efficiency, which is an effective way to solve the problem of infrared imaging guidance target detection in complex environments. Single Shot MultiBox Detector (SSD) is a classic single-stage detection model. The SSD target detection model can be decomposed into two modules: feature extractor and target d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/253
Inventor 刘刚刘森刘中华肖春宝曹紫绚张文波张培根许来祥
Owner HENAN UNIV OF SCI & TECH
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