Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation

TL;DR

This paper introduces a novel method for estimating the 3D pose and location of vehicles from a single 2D image by matching 2D ellipses to 3D circles, demonstrating high accuracy in experiments.

Contribution

It presents a new technique for reliable ellipse detection and a geometric matching method to infer 3D object pose from 2D images, specifically applied to vehicle pose estimation.

Findings

High pose recovery accuracy on synthetic car images

Promising results on real vehicle images

High success rate in identifying car wheels

Abstract

Finding the three-dimensional representation of all or a part of a scene from a single two dimensional image is a challenging task. In this paper we propose a method for identifying the pose and location of objects with circular protrusions in three dimensions from a single image and a 3d representation or model of the object of interest. To do this, we present a method for identifying ellipses and their properties quickly and reliably with a novel technique that exploits intensity differences between objects and a geometric technique for matching an ellipse in 2d to a circle in 3d. We apply these techniques to the specific problem of determining the pose and location of vehicles, particularly cars, from a single image. We have achieved excellent pose recovery performance on artificially generated car images and show promising results on real vehicle images. We also make use of the ellipse detection method to identify car wheels from images, with a very high successful match rate.