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

Confidence map-based method for distinguishing and detecting virtual object of augmented reality scene

A virtual object and augmented reality technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of lack of knowledge, difficulty in discrimination and detection, inapplicability of virtual and real classification, etc., and achieve the effect of wide applicability

Inactive Publication Date: 2013-03-20
BEIHANG UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The above-mentioned methods for distinguishing virtual images from real images have in common that none of the features extracted by them for the virtual-real classification are suitable for any given region in the image.
In addition, in existing object detection work, the objects generally dealt with have strong and easy-to-describe appearance features as prior information
Relatively speaking, in the detection of virtual objects in augmented reality scenes, the detection target (that is, the virtual object) does not have explicit prior information that is easy to describe in appearance, such as color, shape, size, etc., so it is difficult to distinguish and detect

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
  • Confidence map-based method for distinguishing and detecting virtual object of augmented reality scene
  • Confidence map-based method for distinguishing and detecting virtual object of augmented reality scene
  • Confidence map-based method for distinguishing and detecting virtual object of augmented reality scene

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0029] Such as figure 1 As shown, the main steps of the present invention are as follows: build the augmented reality scene training data set, and use the physical imaging difference between the virtual object and the real image to select the virtual and real classification feature; on the training data set, use the virtual and real classification feature to extract the augmented reality scene region’s own characteristics, construct a pixel-level virtual-real classifier; on the training data set, use the virtual-real classification feature to extract the regional comparison features of the augmented reality scene, and build a region-level virtual-real classifier; given the test augmented reality scene, use the pixel-level virtual-real The classifier performs small-scale detection to obtain a virtual score map reflecting the virtual and real classification results of each pixel; defines a virtual confidence map, and on the basis of the virtual score map, uses thresholding to obt...

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 relates to a confidence map-based method for distinguishing and detecting a virtual object of an augmented reality scene. The method comprises the following steps of: selecting vitality and reality classification features; constructing a pixel level vitality and reality classifier by means of the vitality and reality classification features; extracting regional comparison features of the augmented reality scene and a real scene respectively by means of the vitality and reality classification features, and constructing a region level vitality and reality classifier; giving a test augmented reality scene, detecting by means of the pixel level vitality and reality classifier and a small-size detection window to acquire a virtual score plot which reflects each pixel vitality and reality classification result; defining a virtual confidence map, and acquiring the virtual confidence map of the test augmented reality scene by thresholding; acquiring the rough shape and the position of a virtual object bounding box according to the distribution situation of high virtual response points in the virtual confidence map; and detecting by means of the region level vitality and reality classifier and a large-size detection window in the test augmented reality scene to acquire a final detection result of the virtual object. The method can be applied to the fields of film and television manufacturing, digital entertainment, education training and the like.

Description

technical field [0001] The invention relates to the fields of image processing, computer vision and augmented reality, in particular to a method for discriminating and detecting a virtual object in an augmented reality scene based on a confidence map. Background technique [0002] Augmented reality is a further extension of virtual reality. With the help of necessary equipment, computer-generated virtual objects and objectively existing real environments coexist in the same augmented reality system, presenting virtual objects and real environments to users from the perspective of sensory and experience effects. An integrated augmented reality environment. With the development of augmented reality technology and the emergence of augmented reality scenes with higher image realism, there is an urgent need for standards and basis for measuring and evaluating the credibility of augmented reality scenes. How to determine whether a scene is an augmented reality scene, and further ...

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 Patents(China)
IPC IPC(8): G06K9/62
Inventor 陈小武赵沁平穆珺王哲
Owner BEIHANG UNIV
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