Sparse sample marking method in jitter environment

A marking method and sample technology, applied in the field of image recognition, can solve problems such as sparse effective samples and unstable video

Active Publication Date: 2020-08-04
CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of this, the purpose of the present invention is to solve the problem of sparse effective samples in surveillance video in a sparsely populated environment, and to provide a method for marking sparse samples in a shaking environment, which can identify specific targets Tagging to increase the effectiveness of your video

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  • Sparse sample marking method in jitter environment
  • Sparse sample marking method in jitter environment
  • Sparse sample marking method in jitter environment

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Embodiment Construction

[0053] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0054] see Figure 1 ~ Figure 2 , figure 1 It is a method for marking sparse samples in a dithering environment, including: (1) de-jittering algorithm; (2) ...

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Abstract

The invention relates to a sparse sample marking method in a jitter environment, and belongs to the technical field of image recognition. The method comprises the following steps: S1, adopting a de-jittering algorithm to de-jittering an input video file; s2, recognizing a sparse sample by using an improved Mask fast RCNN model; s3, constructing an intelligent marking system, and manually marking the identified sparse samples; and S4, updating the training set: returning the marked data to the training data set for the next round of improved Mask fast RCNN model training. Aiming at the problemof sparse effective samples in a monitoring video in a sparsely populated environment, and considering the video instability difficulty caused by a jittering environment, a specific target can be marked, and the effectiveness of the video is improved.

Description

technical field [0001] The invention belongs to the technical field of image recognition and relates to a method for marking sparse samples in a shaking environment. Background technique [0002] For some specific scenes, the frequency of the target entering and exiting the camera is low, and it is easy to cause a jittery environment, resulting in fewer recognition samples collected, which will lead to low efficiency of the recognition algorithm. At present, common recognition methods for samples in videos rarely consider the impact of fewer recognition samples on recognition accuracy. Therefore, developing a labeling method for sparse samples can help improve object recognition in this specific scenario. Contents of the invention [0003] In view of this, the purpose of the present invention is to solve the problem of sparse effective samples in surveillance video in a sparsely populated environment, and to provide a method for marking sparse samples in a shaking environ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/32G06N3/04G06N3/08G06T3/00G06T5/00
CPCG06T3/0006G06T5/002G06T5/003G06N3/08G06V10/25G06V10/757G06N3/045G06F18/2415G06F18/214
Inventor 张学睿张帆姚远郑志浩
Owner CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
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