Proving the efficiency of template matching-based markerless tracking methods which consider the camera perspective deformations
Egileak: Alex García Alonso
Data: 01.05.2018
Machine Vision and Applications
Abstract
Template matching techniques are often used for camera tracking. They provide a good balance between computational cost and robustness to illumination changes. However, they lack robustness to camera orientation and scale changes. Camera movement, and specially rotation, generates perspective deformations that affect the process of patch matching, so the number of inliers (3D-2D correspondences) decreases. This fact affects camera tracking stability. This paper provides the following statistical proof: considering surface normals associated with 3D points substantially increases the number of inliers. So, this paper shows that computing perspective compensation improves the tracking. For instance, in a particular camera path used for experiments in this paper, without compensation, only a of 3D points projected into the image were found as inliers, while perspective compensation increased that figure up to a . These results must be contextualized in the analysis provided by the paper.
BIB_text
title = {Proving the efficiency of template matching-based markerless tracking methods which consider the camera perspective deformations},
journal = {Machine Vision and Applications},
pages = {573-584},
volume = {29},
keywds = {
Surface normal; Template matching; Perspective compensation; Visual tracking
}
abstract = {
Template matching techniques are often used for camera tracking. They provide a good balance between computational cost and robustness to illumination changes. However, they lack robustness to camera orientation and scale changes. Camera movement, and specially rotation, generates perspective deformations that affect the process of patch matching, so the number of inliers (3D-2D correspondences) decreases. This fact affects camera tracking stability. This paper provides the following statistical proof: considering surface normals associated with 3D points substantially increases the number of inliers. So, this paper shows that computing perspective compensation improves the tracking. For instance, in a particular camera path used for experiments in this paper, without compensation, only a of 3D points projected into the image were found as inliers, while perspective compensation increased that figure up to a . These results must be contextualized in the analysis provided by the paper.
}
doi = {10.1007/s00138-018-0914-2},
date = {2018-05-01},
}
