A High-Resolution Network-Based Approach for 6D Pose Estimation of Industrial Parts

Junming Fan, Shufei Li, Pai Zheng, Carman K.M. Lee

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

The estimation of 6D pose of industrial parts is a fundamental problem in smart manufacturing. Traditional approaches mainly focus on matching corresponding key point pairs between observed 2D images and 3D object models via hand-crafted feature descriptors. However, key points are hard to discover from images when the parts are piled up in disorder or occluded by other distractors, e.g., human hands. Although the emerging deep learning-based methods are capable of inferring the poses of occluded parts, the accuracy is not satisfactory largely due to the loss of spatial resolution from multiple downsampling operations inside convolutional neural networks. To overcome this challenge, this paper proposes a 6D pose estimation model consisting of a pose estimator and a pose refiner, by leveraging High-Resolution Networks as the backbone. Experiments are further conducted on a dataset of industrial parts to demonstrate its effectiveness.

Original languageEnglish
Title of host publication2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021
PublisherIEEE Computer Society
Pages1452-1457
Number of pages6
ISBN (Electronic)9781665418737
DOIs
Publication statusPublished - 23 Aug 2021
Event17th IEEE International Conference on Automation Science and Engineering, CASE 2021 - Lyon, France
Duration: 23 Aug 202127 Aug 2021

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2021-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference17th IEEE International Conference on Automation Science and Engineering, CASE 2021
Country/TerritoryFrance
CityLyon
Period23/08/2127/08/21

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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