Sciweavers

Share
CORR
2010
Springer

Featureless 2D-3D Pose Estimation by Minimising an Illumination-Invariant Loss

9 years 4 months ago
Featureless 2D-3D Pose Estimation by Minimising an Illumination-Invariant Loss
The problem of identifying the 3D pose of a known object from a given 2D image has important applications in Computer Vision ranging from robotic vision to image analysis. 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 neither require prior training nor learning, nor knowledge of the camera parameters, nor explicit point correspondences or matching features between 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, and works on a single static image from a given view, and under varying and unknown lighting conditions. For this purpose we derive a novel illumination-invariant distance measure between 2D photo and projected 3D model, which is then minimised to find the best pose parameters. Results for vehicle pose detection are presented....
Srimal Jayawardena, Marcus Hutter, Nathan Brewer
Added 01 Mar 2011
Updated 01 Mar 2011
Type Journal
Year 2010
Where CORR
Authors Srimal Jayawardena, Marcus Hutter, Nathan Brewer
Comments (0)
books