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

Space salient region extraction method based on depth variation model

A variational model and region extraction technology, applied in the field of computer vision, can solve problems such as emphasizing

Inactive Publication Date: 2015-01-28
BEIJING UNIV OF TECH
View PDF4 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] 3D reconstruction technology is a very important application in today's vision, but most of the existing technologies focus on the overall scene reconstruction

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 salient region extraction method based on depth variation model
  • Space salient region extraction method based on depth variation model
  • Space salient region extraction method based on depth variation model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0107] Below in conjunction with accompanying drawing, the patent of the present invention is described in further detail.

[0108] The flow chart of the spatially salient region extraction method based on the deep variational model is shown in Figure (1), which specifically includes the following steps.

[0109] Step 1, camera calibration.

[0110] Establish the camera projection model, use the FOV model to realize the correction of the monocular camera, map the image pixel coordinates to the normalized coordinate plane, and combine the camera internal parameter matrix K to realize image distortion correction, namely: u=Kx n .

[0111] Step 2, the establishment and solution of the depth model.

[0112] Under the premise of PTAM accurate pose estimation, the depth map estimation algorithm based on the variational model is adopted to obtain the three-dimensional information of the current environment. Based on the variational optical flow estimation algorithm, the method com...

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 belongs to the field of computer vision and relates to a space salient region extraction method based on a depth variation model. The method comprises the steps of firstly, correcting a camera, selecting a keyframe image sequence in an image, acquiring an original depth image with the discrete space sampling method, and constructing the energy function of a depth estimation model under the variation mode; then, solving the energy function with the primal-dual algorithm to achieve optimization of the depth model; conducting rough salient region extraction on the optimized depth image with the salient filter algorithm, and optimizing a salient region by means of an improved pulse coupling neural network to achieve accurate extraction of the depth salient region; finally, reconstructing a three-dimensional salient area. According to the method, based on the relevance between different coordinate systems under a specific visual angle and the perspective projection transformation relation of the camera, the energy function contains multi-view image restraint, the computation complexity of solving of an algorithm model is reduced, and depth image estimation quality is improved.

Description

technical field [0001] The invention belongs to the field of computer vision and relates to a method for extracting spatially salient regions based on a depth variation model. Background technique [0002] In our daily life, when we observe images, we are usually only interested in a small and salient part of the whole image or the whole video. Therefore, when the computer simulates the human visual system, it mainly simulates by detecting salient regions in the image. Saliency detection has gradually become a very important technology in the field of computer vision. In this field, how to use efficient methods to accurately detect and reconstruct spatially salient regions from large scenes is a very critical technology. There are many traditional saliency detection methods, but for some images, for example, there are close-up and distant views in the image, and the distant view is far away from the observer, the results of saliency detection for such images are not very c...

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): G06T7/00
CPCG06T7/55G06T2207/10016
Inventor 贾松敏徐涛张鹏李秀智宣璇
Owner BEIJING UNIV OF TECH
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com