@inbook {2101, title = {3D Reconstruction of Planar Surface Patches: A Direct Solution}, booktitle = {Proceedings of the ACCV Workshop on Big Data in 3D Computer Vision (ACCV-BigData3DCV)}, year = {2014}, month = {Nov 2014}, pages = {1-8.}, publisher = {Springer}, organization = {Springer}, type = {Conference paper}, address = {Singapore, Szingap{\'u}r}, author = {Jozsef Molnar and Rui Huang and Zoltan Kato}, editor = {Jian Zhang and Mohammed Bennamoun and Fatih Porikli} } @inbook {1302, title = {Targetless Calibration of a Lidar - Perspective Camera Pair}, booktitle = {Proceedings of ICCV Workshop on Big Data in 3D Computer Vision}, year = {2013}, note = {doi: 10.1109/ICCVW.2013.92}, month = {Dec 2013}, pages = {668 - 675}, publisher = {IEEE}, organization = {IEEE}, type = {Conference paper}, address = {Sydney, NSW }, abstract = {

A novel method is proposed for the calibration of a camera - 3D lidar pair without the use of any special calibration pattern or point correspondences. The proposed method has no specific assumption about the data source: plain depth information is expected from the lidar scan and a simple perspective camera is used for the 2D images. The calibration is solved as a 2D-3D registration problem using a minimum of one (for extrinsic) or two (for intrinsic-extrinsic) planar regions visible in both cameras. The registration is then traced back to the solution of a non-linear system of equations which directly provides the calibration parameters between the bases of the two sensors. The method has been tested on a large set of synthetic lidar-camera image pairs as well as on real data acquired in outdoor environment.

}, doi = {10.1109/ICCVW.2013.92 }, author = {Tam{\'a}s Levente and Zoltan Kato}, editor = {Jian Zhang and Mohammed Bennamoun and Dan Schonfeld and Zhengyou Zhang} }