Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy

07/01/2022
by   Jun Wu, et al.
0

Current RGB-based 6D object pose estimation methods have achieved noticeable performance on datasets and real world applications. However, predicting 6D pose from single 2D image features is susceptible to disturbance from changing of environment and textureless or resemblant object surfaces. Hence, RGB-based methods generally achieve less competitive results than RGBD-based methods, which deploy both image features and 3D structure features. To narrow down this performance gap, this paper proposes a framework for 6D object pose estimation that learns implicit 3D information from 2 RGB images. Combining the learned 3D information and 2D image features, we establish more stable correspondence between the scene and the object models. To seek for the methods best utilizing 3D information from RGB inputs, we conduct an investigation on three different approaches, including Early- Fusion, Mid-Fusion, and Late-Fusion. We ascertain the Mid- Fusion approach is the best approach to restore the most precise 3D keypoints useful for object pose estimation. The experiments show that our method outperforms state-of-the-art RGB-based methods, and achieves comparable results with RGBD-based methods.

READ FULL TEXT

page 1

page 3

page 4

page 5

page 8

research
09/25/2021

Learning Stereopsis from Geometric Synthesis for 6D Object Pose Estimation

Current monocular-based 6D object pose estimation methods generally achi...
research
04/11/2020

A Novel Pose Proposal Network and Refinement Pipeline for Better Object Pose Estimation

In this paper, we present a novel deep learning pipeline for 6D object p...
research
01/15/2019

DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion

A key technical challenge in performing 6D object pose estimation from R...
research
09/24/2019

6D Pose Estimation with Correlation Fusion

6D object pose estimation is widely applied in robotic tasks such as gra...
research
08/12/2020

PAM:Point-wise Attention Module for 6D Object Pose Estimation

6D pose estimation refers to object recognition and estimation of 3D rot...
research
09/15/2020

BOP Challenge 2020 on 6D Object Localization

This paper presents the evaluation methodology, datasets, and results of...
research
11/01/2021

Learning Eye-in-Hand Camera Calibration from a Single Image

Eye-in-hand camera calibration is a fundamental and long-studied problem...

Please sign up or login with your details

Forgot password? Click here to reset