Bennett, S and Lasenby, J (2013) Robust recognition of chess-boards under deformation. 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings. pp. 2650-2654.Full text not available from this repository.
Current methods for formation of detected chess-board vertices into a grid structure tend to be weak in situations with a warped grid, and false and missing vertex-features. In this paper we present a highly robust, yet efficient, scheme suitable for inference of regular 2D square mesh structure from vertices recorded both during projection of a chess-board pattern onto 3D objects, and in the more simple case of camera calibration. Examples of the method's performance in a lung function measuring application, observing chess-boards projected on to patients' chests, are given. The method presented is resilient to significant surface deformation, and tolerates inexact vertex-feature detection. This robustness results from the scheme's novel exploitation of feature orientation information. © 2013 IEEE.
|Uncontrolled Keywords:||camera calibration Grid finding rotational constraints structured light surface reconstruction|
|Divisions:||Div F > Signal Processing and Communications|
|Depositing User:||Unnamed user with email firstname.lastname@example.org|
|Date Deposited:||16 Jul 2015 13:33|
|Last Modified:||03 Aug 2015 00:49|