3D Object Localization Using 2D Estimates for Computer Vision Applications

TL;DR

This paper introduces a method for 3D object localization by estimating 3D coordinates from multiple 2D images, using camera calibration and pose estimation techniques, validated through MATLAB experiments.

Contribution

It presents a novel approach combining 2D image analysis with camera calibration for accurate 3D object localization.

Findings

Effective 3D pose estimation demonstrated

Camera calibration improves localization accuracy

Validated with MATLAB experiments

Abstract

A technique for object localization based on pose estimation and camera calibration is presented. The 3-dimensional (3D) coordinates are estimated by collecting multiple 2-dimensional (2D) images of the object and are utilized for the calibration of the camera. The calibration steps involving a number of parameter calculation including intrinsic and extrinsic parameters for the removal of lens distortion, computation of object's size and camera's position calculation are discussed. A transformation strategy to estimate the 3D pose using the 2D images is presented. The proposed method is implemented on MATLAB and validation experiments are carried out for both pose estimation and camera calibration.