What is 6D Object Pose Estimation in Computer Vision?

Photo by Arvin Mantilla on Unsplash

Introduction

Object Pose Estimation (OPE) is a typical task in computer vision that consists of identifying specific object instances in an image and determining each object’s position and orientation relative to some coordinate system. The pose of an object in a 3D scene can be described by means of rotation and translation transformation.

6D object pose estimation (L) The goal of 6D pose estimation is to find the translation and rotation from the object coordinate frame O to the camera coordinate frame C. (R) The translation and rotation both have three degrees of freedom,

However, using this type of fixed 3D orientation representation can cause pose ambiguities due to symmetries. An overview of the different causes of pose ambiguities is shown in the figure below.

Causes of pose ambiguities

State-of-the-Art Overview

In literature, 6D object pose estimation algorithms from a single RGB image can be divided into three main categories using traditional image processing techniques or deep learning: