Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Lens shielding discrimination method based on semantic analysis

A technology of lens occlusion and discrimination method, applied in the field of image recognition, can solve problems such as difficulty in discriminating lens occlusion, and achieve the effect of eliminating the interference of meaningless features, reducing the demand for data volume, and fast convergence.

Pending Publication Date: 2022-01-28
CHINACCS INFORMATION IND
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, it is difficult to judge the lens occlusion by target detection and image classification alone.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Lens shielding discrimination method based on semantic analysis
  • Lens shielding discrimination method based on semantic analysis
  • Lens shielding discrimination method based on semantic analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] Embodiment one, see Figure 1-Figure 2 , the present invention is achieved through the following technical solutions: a method for discriminating lens occlusion based on semantic analysis, comprising the following steps:

[0035] S1, collecting an occlusion data set, marking the monitoring area and occlusions of the surveillance camera, and training a target detection network according to the occlusion data set;

[0036] The details are as follows: First, mark a batch of monitoring scene image data sets, mark the main monitoring area of ​​the camera, and train the target detection network so that it can robustly detect the monitoring area;

[0037] Add occluder labels to the above data set and continue training so that the model can detect occluders;

[0038] S2. Use the trained target detection network to detect the monitoring screen; use the target detection algorithm Faster-RCNN to detect the position, size and appearance of the "monitoring area" and the occluder, a...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a lens occlusion discrimination method based on semantic analysis, and belongs to the technical field of image recognition. According to the technical scheme, the lens occlusion judgment method based on semantic analysis comprises the steps that a deep convolution detection network is trained, monitoring areas and occlusion objects are detected, the monitoring areas and the multiple occlusion objects are paired into multiple semantic relation pairs in a one-to-many mode, the sum of relation pair detection frames formed by combining subjects and objects is a relation external connection frame, and the sum of the relation pair detection frames is the relation external connection frame. And mapping to a top feature map of the backbone convolutional neural network, deducting the feature map by using a ROIAlign algorithm, mapping to a fixed size, and sending the feature map to a semantic discrimination full-connection layer for relation prediction. And finally, predicting and judging whether the current lens is shielded or not according to whether the prediction result contains shielding or not. The beneficial effects of the invention are that the method is used for decomposing the classification problem of lens shielding into a detection / relation prediction problem, is higher in interpretability, and can accurately judge the position relation between a shielding object and a monitoring area.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a method for judging lens occlusion based on semantic analysis. Background technique [0002] At present, the control camera is the core device used in the construction of safe cities and safe communities. As time goes by, the environment where the cameras were installed in the early years may have changed a lot, and some are even blocked by (such as dense branches and leaves). Thousands of cameras are inspected manually one by one, which is laborious and may be missed due to fatigue of personnel. Ordinary classification or detection algorithms, camera lens occlusion detection related algorithms are very few, indicating that it is not easy for a computer to judge this problem. Currently, only a few algorithms detect whether the lens is occluded by detecting the presence of leaves. This method has two limitations: first, there is no necessary connection between the foc...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/10G06V20/52G06V10/774G06V10/764G06V10/80G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/214G06F18/253G06F18/24
Inventor 蒋海军马新成张宝石权秀琼
Owner CHINACCS INFORMATION IND
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products