Indoor scene layout estimation and target region extraction method based on RGB-D images

A technology for target areas and indoor scenes, applied in the field of artificial intelligence computing, can solve problems such as complex layout estimation and target extraction, and achieve the effect of improving segmentation effect, fast calculation speed, and easy implementation.

Active Publication Date: 2017-11-21
NANJING UNIV OF POSTS & TELECOMM
View PDF4 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the shortcomings of the above-mentioned prior art, the present invention takes into account the recall rate and rapidity, and solves the problems of layout estimation and target extractio

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
  • Indoor scene layout estimation and target region extraction method based on RGB-D images
  • Indoor scene layout estimation and target region extraction method based on RGB-D images
  • Indoor scene layout estimation and target region extraction method based on RGB-D images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0018] figure 1 It is an overall flow chart of the RGB-D image-based indoor scene layout estimation and target area extraction method proposed by the embodiment of the present invention. The steps of this embodiment are as follows

[0019] Step (1) Scene layout estimation: first convert the depth map into a dense 3D point cloud, such as figure 2 As shown in , then the planar area and non-planar area are divided into planar area and non-planar area by calculating the three-dimensional Euclidean distance between point clouds, and the obtained planar area is classified into boundary plane and non-b...

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 present invention discloses an indoor scene layout estimation and target region extraction method based on RGB-D images. The method comprises the following steps: performing scene layout estimation; using a graph-based segmentation algorithm and a constraint parameter minimum-cut algorithm to perform over segmentation of the processed depth map and RGB images to get the region sets of different sizes; performing over-segmentation level grouping, using four different similarity measurement modes to perform regional combination to complete the regional level grouping, so as to access to target regions of all sizes; and performing target boundary-box matching. The method realizes the target region extraction of the indoor scene with high efficiency and high recall rate.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence computing, in particular to a RGB-D image-based indoor scene layout estimation and target area extraction method, which is applied to indoor service robot technology. Background technique [0002] The research on indoor scene analysis is one of the research hotspots of scholars at home and abroad. It has important application value for indoor robot semantic positioning and map generation, and it is also of great significance for solving some advanced computer vision problems. The object segmentation and extraction algorithm aims to obtain high-quality object location and instance segmentation results, which is one of the key steps in scene analysis. The target extraction result is usually a target candidate area or a target bounding box. After years of development, target extraction algorithms can be divided into two categories: the first is an algorithm based on the idea of ​​slid...

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): G06T7/11G06T7/13G06T7/50G06K9/00
CPCG06T7/11G06T7/13G06T7/50G06T2207/10024G06T2207/10028G06T2207/20024G06V20/10
Inventor 吴晓秋霍智勇
Owner NANJING UNIV OF POSTS & TELECOMM
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