GCN-Calculated Graph-Feature Embedding for 3D Endoscopic System Based on Active Stereo

Michihiro Mikamo, Hiroshi Kawasaki, Ryusuke Sagawa, Ryo Furukawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

One of the promising fields for active-stereo sensors is medical applications such as 3D endoscope systems. For such systems, robust correspondence estimation between the detected patterns and the projected pattern is the most crucial. In this paper, we propose an auto-calibrating 3D endoscopic system using a 2D grid-graph pattern, where codes are embedded into each grid point. Since the pattern is a grid graph, we use a graph convolutional network (GCN) to calculate node-wise embedding accumulating code information of nearby grid points in the graph. The correspondence estimation using the GCN-calculated feature embedding is shown to be stable, even without using epipolar constraints. Using the correspondence estimation, we show that the auto-calibrating 3D measurement system can be realized. In the experiment, we confirmed that the proposed system achieved high accuracy and robust estimation comparing to the previous methods.

Original languageEnglish
Title of host publicationFrontiers of Computer Vision - 27th International Workshop, IW-FCV 2021, Revised Selected Papers
EditorsHieyong Jeong, Kazuhiko Sumi
PublisherSpringer Science and Business Media Deutschland GmbH
Pages253-266
Number of pages14
ISBN (Print)9783030816377
DOIs
Publication statusPublished - 2021
Event27th International Workshop on Frontiers of Computer Vision, IW-FCV 2021 - Virtual, Online
Duration: Feb 22 2021Feb 23 2021

Publication series

NameCommunications in Computer and Information Science
Volume1405
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference27th International Workshop on Frontiers of Computer Vision, IW-FCV 2021
CityVirtual, Online
Period2/22/212/23/21

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

Fingerprint

Dive into the research topics of 'GCN-Calculated Graph-Feature Embedding for 3D Endoscopic System Based on Active Stereo'. Together they form a unique fingerprint.

Cite this