Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Space-time multiple feature based vehicle shadow eliminating method

A shadow elimination and multi-feature technology, which is applied in the field of intelligent transportation and computer vision, can solve the problems of missing detection and high requirements for texture restoration

Inactive Publication Date: 2017-01-18
UNIV OF ELECTRONIC SCI & TECH OF CHINA
View PDF3 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method requires a high degree of texture restoration of the reference background image. In the case of texture loss during the background reconstruction process, this method is prone to large-scale missed detection.

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
  • Space-time multiple feature based vehicle shadow eliminating method
  • Space-time multiple feature based vehicle shadow eliminating method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the implementation methods and accompanying drawings.

[0045] see figure 1 , the vehicle shadow elimination method based on spatio-temporal multi-features of the present invention, comprises the following steps:

[0046] Step 1: input the video frame I to be processed;

[0047] Step 2: Model the background of the current video frame I (hereinafter referred to as image I), obtain the background image B and calculate the corresponding initial foreground area F 0 .

[0048] Step 3: Calculate the foreground mask F of the three features of chromaticity, spectral direction and texture respectively chr , F phy , F tex .

[0049] Step 301: Calculate the foreground mask F of the color feature chr .

[0050] When calculating the foreground mask of the chromaticity feature, this embodiment tak...

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 space-time multiple feature based vehicle shadow eliminating method. A background image and an initial foreground area of a video frame to be processed are obtained, a foreground mask layer of chroma, spectrum direction and texture features is obtained, weighted summation is carried out to obtain a spatial-domain multi-feature foreground probabilistic spectrum image, time-domain filtering of a time sliding window is carried out on the spatial-domain multi-feature foreground probabilistic spectrum image to obtain a corresponding time-domain foreground probabilistic spectrum, the time-domain foreground probabilistic spectrum is weighted to obtain a final foreground mask layer, and vehicle shadows are eliminated from a video frame image. Compared with a traditional shadow removing method based on a single feature and multi-feature cascading, the shadows are removed more effectively, and a foreground contour is more complete. Both higher shadow identification rate and higher shadow detection ratio are ensured.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation and computer vision, and in particular relates to a video vehicle shadow removal method based on spatio-temporal multi-feature fusion. Background technique [0002] The vehicle elimination method is a key technology in the fields of intelligent transportation and computer vision, and is an important research direction in this field. As the pre-processing link in the intelligent transportation system, vehicle foreground detection plays a vital role in the whole system. During the moving process of the target, the vehicle's adhesion and rough outline formed by the shadow seriously affect the detection of the vehicle, which also brings great difficulties to the subsequent processing. Therefore, it is of great significance to study shadow detection and elimination methods. [0003] For traffic monitoring video sequences, current vehicle shadow removal methods are usually based on ...

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): G06T5/00
CPCG06T2207/20182G06T2207/10016G06T2207/30232G06T5/77
Inventor 王正宁柏祁林韩明燕周阳马姗姗
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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
Eureka Blog
Learn More
PatSnap group products