Supercharge Your Innovation With Domain-Expert AI Agents!

3D scene flow estimation method based on self-adaptive non-local smoothing method

A scene flow, adaptive technology, applied in computing, image data processing, instruments, etc., to achieve the effect of removing heterogeneous points

Active Publication Date: 2017-03-15
HARBIN ENG UNIV
View PDF2 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to smooth the flow field at each level of iteration by calculating the average value of the Euclidean distance of all similar points in the flow field point neighborhood, so as to solve the shortcomings in the existing scene flow model based on adaptive non-local Smooth 3D Scene Flow Estimation Method

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
  • 3D scene flow estimation method based on self-adaptive non-local smoothing method
  • 3D scene flow estimation method based on self-adaptive non-local smoothing method
  • 3D scene flow estimation method based on self-adaptive non-local smoothing method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055] The present invention will be described in more detail below in conjunction with the accompanying drawings.

[0056] The present invention comprises the following steps:

[0057] S1. According to the correspondence between stereoscopic image sequences acquired by binocular cameras, the local constraint method is combined with global smoothing, and adaptive non-local smoothing is introduced to construct a scene flow energy functional.

[0058] S2. Referring to the Lucas model, design scene flow data items with local neighborhood constraints, the data items meet the assumption of brightness invariance, and introduce a robust penalty function to remove the influence of out-of-set points.

[0059] S3. The smoothing item uses a robust function to construct a full variational smoothing approximate to the L1 norm, and introduces an adaptive non-local smoothing S MF , smoothing the flow field at each layer of the iteration, eliminating image noise and environmental noise, and ...

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 machine vision, and particularly relates to a 3D scene flow estimation method based on the self-adaptive non-local smoothing method. The method comprises the steps of according to the corresponding relation between stereoscopic image sequences acquired by a binocular camera, combining the local constraint method with the global smoothing method and introducing the self-adaptive non-local smoothing method; in reference to a Lucas model, designing scene flow data items for the local neighborhood constrains; adopting the robust function as a smooth item to construct a total variation smoothing approximate to an L1 norm; and solving out an energy function in the de-antithesis manner. According to the technical scheme of the invention, noise-induced heterogeneous points in an image sequence can be effectively removed, and the edge information of the motion field can be maintained. Meanwhile, the information can be effectively transmitted to a low-texture region.

Description

technical field [0001] The invention belongs to the field of machine vision, and in particular relates to a 3D scene flow estimation method based on adaptive non-local smoothing. Background technique [0002] The world we live in is complex and changeable, and in the process of human understanding of the world, most of the information comes from vision. With the rapid development of computer technology and sensors, machine vision has become an important part of human beings to realize automatic data collection, and it is widely used in military, medical and civilian fields. In the visual field, moving objects contain more information than stationary objects, and the motion flow field builds a bridge from low-level information to high-level image analysis. [0003] The optical flow field cleverly realizes the estimation of the motion of the object by combining the brightness of the object and the motion field, but it loses the information in the depth direction, which is not...

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
CPCG06T2207/20192G06T5/70
Inventor 项学智白二伟徐旺旺颜子轲肖德广李佳佳盛玉娇魏依萌张磊乔玉龙
Owner HARBIN ENG UNIV
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com