Video-based weather phenomenon recognition method

A recognition method and phenomenon technology, applied in the field of video-based weather phenomenon recognition, can solve the problem of relatively few researches on weather phenomenon recognition methods

Active Publication Date: 2015-03-25
PLA UNIV OF SCI & TECH
View PDF2 Cites 30 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

So far, relatively little research has been done on

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
  • Video-based weather phenomenon recognition method
  • Video-based weather phenomenon recognition method
  • Video-based weather phenomenon recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0126] This embodiment includes offline classifier training and online weather phenomenon recognition, and its processing flow chart is as follows figure 1 As shown, the whole method is divided into two main steps of offline classifier training and online weather phenomenon recognition, and the main process of the embodiment part is introduced respectively below.

[0127] 1. Offline classifier training

[0128] First, manually label the collected video library, and select 100 sets of image sequences from the image sequences of each type of weather phenomenon as training samples, each group contains 100 frames of images, including weather phenomena sunny, foggy, cloudy, rainy and The sample images of snow video frames are shown in Fig. 2 respectively.

[0129] When extracting the video feature of the video according to step 11, extract the correlation feature according to step 111, the correlation function diagram of a certain sub-region is as follows image 3 As shown, the c...

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 discloses a video-based weather phenomenon recognition method. The method achieves classification recognition of common weather phenomena such as sun, cloud, rain, snow and fog. The method comprises the steps of training an off-line classifier, wherein an image sequence is sampled for a given training video; on the one hand, video characteristics of the image sequence are extracted; on the other hand, key frame images and image characteristics of the key frame images are extracted from the image sequence, the AdaBoost is adopted for conducting learning and training on the extracted video characteristics, the extracted image characteristics and manual annotations to obtain the classifier; recognizing the weather phenomena in an online mode, wherein a plurality of sets of image sequences are sampled for a testing video, video characteristics and image characteristics of each set of image sequences are extracted, the characteristics are sent into the classifier for classification to obtain a corresponding recognition result, then decision fusion is carried out in a voting mode, and the voting result is used as the weather phenomenon recognition result of the testing video.

Description

technical field [0001] The invention relates to a weather phenomenon recognition method, which belongs to the technical field of ground meteorological observation in atmospheric detection, in particular to a video-based weather phenomenon recognition method. Background technique [0002] Weather phenomena refer to the atmosphere or physical processes related to the atmosphere that occur on and above the ground, and are an important part of surface meteorological observations. At present, conventional meteorological elements such as temperature, humidity, wind direction, wind speed, air pressure, and rainfall have been automatically detected. Disadvantages such as low frequency, high cost and limited observation range. The invention utilizes the rich visual information in the video captured by the fixed monitoring camera to study the detection and identification of weather phenomena such as sunny, cloudy, rain, snow, fog, etc., and explores the video-based off-line classifie...

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
IPC IPC(8): G06K9/62
CPCG06F18/2413
Inventor 李骞夏士明胡友彬盛宝隽
Owner PLA UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap