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High-accuracy intelligent identification target tracking system and method for security camera

A technology of intelligent recognition and target tracking, applied in character and pattern recognition, instruments, biological neural network models, etc., can solve problems such as imbalance

Pending Publication Date: 2021-04-06
WUHAN INSTITUTE OF TECHNOLOGY
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AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a high-precision intelligent identification target tracking system and method for security cameras, which are used to solve the problem of class imbalance and realize a robust visual tracking function

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  • High-accuracy intelligent identification target tracking system and method for security camera
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  • High-accuracy intelligent identification target tracking system and method for security camera

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Embodiment Construction

[0053] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0054] see figure 1 , the initial neural network model of a high-accuracy intelligent recognition target tracking system for security cameras in an embodiment of the present invention is a twin cascaded RPN, including sequentially connected twin neural network modules and cascaded RPN modules, and also includes image input modules, feature Transfer module FTB, tracking result display module, target information module.

[0055] The Siamese neural network module is used to extract features from the target template Z and the search region X.

[0056] The cascaded RPN module is used to make full use of the multi-level features of each RPN for sequence classification and regression, to solve the problem of background interference sources that appear during the tracking process, and because the targets belong to the same category and / or ha...

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Abstract

The invention provides a high-accuracy intelligent identification target tracking system and method for a security camera, and the system and method solve a problem of class imbalance through the cascading of a series of RPN (Region Proposal Network), achieve the full mining of cross-layer features, and achieve a stable visual tracking function. According to the invention, a new multi-stage tracking framework, namely the twin cascaded RPN, is proposed for the first time, a tracker based on the twin cascaded RPN is achieved, the recognition capability of the twin cascaded RPN for utilizing advanced semantic information and low-level spatial information is further improved, and through multi-step regression, the positioning is more accurate, and the distribution sequence of training samples is more balanced; the classifier of the RPN is more discriminative in sequence when more difficult interferents are distinguished, and target positioning is more accurate and has real-time performance under a complex background.

Description

technical field [0001] The invention belongs to the technical field of security cameras, and in particular relates to a high-precision intelligent identification target tracking system and method for security cameras. Background technique [0002] In terms of object tracking, Siamese-RPN has achieved good results, but may drift to the background, especially in the presence of similar semantic interference. There are two main reasons: [0003] First, the distribution of training samples is unbalanced: (1) the positive samples are much smaller than the negative samples, resulting in invalid Siamese network training; (2) most of the negative samples are simple negative samples (non-similar non-semantic backgrounds), which are important in learning to distinguish There is little useful information when using a classifier. Therefore, the classifier is dominated by easily classified background samples, and the performance of the classifier degrades when encountering difficult si...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/241G06F18/253G06F18/214
Inventor 吴锦梦李兴珣陈翩翩舒鹏程
Owner WUHAN INSTITUTE OF TECHNOLOGY
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