A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation

Date

2011

Authors

Jayawardena, Srimal
Hutter, Marcus
Brewer, Nathan

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE Communications Society

Abstract

The problem of identifying the 3D pose of a known object from a given 2D image has important applications in Computer Vision. Our proposed method of registering a 3D model of a known object on a given 2D photo of the object has numerous advantages over existing methods. It does not require prior training, knowledge of the camera parameters, explicit point correspondences or matching features between the image and model. Unlike techniques that estimate a partial 3D pose (as in an overhead view of traffic or machine parts on a conveyor belt), our method estimates the complete 3D pose of the object. It works on a single static image from a given view under varying and unknown lighting conditions. For this purpose we derive a novel illumination-invariant distance measure between the 2D photo and projected 3D model, which is then minimised to find the best pose parameters. Results for vehicle pose detection in real photographs are presented.

Description

Keywords

Keywords: 2D-3D pose estimation; 3D models; featureless; Monocular; Optimisations; pixel-based; Belt conveyors; Computer applications; Photography; Three dimensional 2D-3D pose estimation; 3D Model; featureless; illumination-invariant loss; Monocular; optimisation; pixel-based

Citation

Source

A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation

Type

Conference paper

Book Title

Entity type

Access Statement

License Rights

DOI

10.1109/DICTA.2011.15

Restricted until

2037-12-31