RGB-D visual-odometer method based on Census transformation and local-graph optimization

A visual odometry and partial map technology, applied in the field of computer vision, can solve problems such as scale drift, can only be used indoors, and the range of depth measurement is limited, so as to improve robustness and accuracy, and solve the lack of depth information , Optimizing the effect of estimation accuracy

Active Publication Date: 2018-05-08
SUN YAT SEN UNIV
View PDF3 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The visual odometry method based on a pure monocular camera is relatively complicated. It also needs to reconstruct the three-dimensional map points while estimating the pose, and the estimated pose and three-dimensional points have no absolute scale, which is prone to scale drift and requires better initialization.
The binocular camera can obtain the depth value of the pixel in the image scene through binocular stereo mat

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
  • RGB-D visual-odometer method based on Census transformation and local-graph optimization
  • RGB-D visual-odometer method based on Census transformation and local-graph optimization
  • RGB-D visual-odometer method based on Census transformation and local-graph optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] The present invention will be further described below in conjunction with accompanying drawing and embodiment, but the embodiment of the present invention is not limited thereto.

[0043] A RGB-D visual odometry method based on Census transformation and partial graph optimization, such as figure 1 As shown in Figure 2, it includes the following steps:

[0044] S1. Obtain the color and depth image information of the environment through the RGB-D sensor, and use the color image to calculate the Census description map;

[0045] S2. Based on the Census description map, use the direct method to perform motion estimation on the current frame, and calculate the relative pose of the current frame and the latest key frame in the local map;

[0046] S3. For points with significant gradient information but lack of depth information in the local map, perform depth tracking estimation in the current frame;

[0047] S4. According to the pose estimation result of the current frame, ...

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 an RGB-D visual-odometer method based on Census transformation and local-graph optimization. The method includes the following steps: acquiring color and depth image information of an environment through an RGB-D sensor, and using color images to calculate Census description graphs; using a direct method to carry out motion estimation on a current frame on the basis of a Census description graph, and calculating a relative pose of the current frame and a newest key frame in local graphs; for points, of which gradient information is significant but depth information islacking, in the local graphs, carrying out depth tracking estimation in the current frame; and generating a new key frame according to a pose estimation result of the current frame, inserting the sameinto the local graphs, and carrying out graph optimization and key-frame management operations on the local graphs. According to the method, the Census description graphs are used for direct-method motion estimation, optimization and management of the local graphs are combined, and real-time robustness of a visual odometer in color-image brightness changing and depth-image depth information deficiency is improved.

Description

technical field [0001] The present invention relates to computer vision technical field, more specifically, relate to a kind of RGB-D visual odometry method based on Census transformation and partial graph optimization. Background technique [0002] Visual odometry is a method of incrementally estimating the trajectory of a person or object fixedly connected to a visual sensor through an input image sequence. Compared with traditional inertial navigation and wheel odometers, visual odometers overcome the measurement error problems of inertial navigation drift and tire slippage, do not need satellite navigation, and visual sensors have the advantages of low power consumption and rich information collected, so Visual odometry has been widely concerned and gradually applied in the field of mobile robot positioning and navigation. [0003] At present, the methods of visual odometry mainly include feature point method and direct method. The main process of the feature point met...

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): G06T7/73G06T7/207G06T5/00
CPCG06T5/002G06T7/207G06T7/73G06T2207/20016
Inventor 陈佩卢德辉谢晓明
Owner SUN YAT SEN UNIV
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