In both RMCS calibration and ACS calibration, the corresponding efficiency and robustness are tested by simulation and real experiments. In the real experiment of ACS calibration, the intrinsic and extrinsic parameters of the ACS are obtained simultaneously by our calibration procedure using the same image sequences, no extra data capturing step is required. The corresponding trajectory is recovered and illustrated using the calibration results of the ACS. Since the estimated translations of different cameras in an MCS may scaled by different scale factors, scale factor estimation algorithms are proposed for non-overlapping view RMCS calibration and ACS calibration respectively. To our knowledge, we are the first to study the calibration of ACS. / In this thesis, we focus on developing robust methods for the MCS calibration problems. In particular, we make two contributions. Firstly, we developed a novel extrinsic calibration method for the non-overlapping view Rigid Multiple Camera System (RMCS) using the kinematic information of the RMCS. The input are only the images captured when the non-overlapping RMCS is moved in an environment with enough static feature points. This assumption is true in many vision tasks such as SFM (Structure from Motion), SLAM (Simultaneous Localization and Map). The output is the extrinsic parameters of the cameras of the RMCS. / Multiple Camera Systems (MCS) have been widely applied in many vision applications and attracted much attention recently. Both intrinsic and extrinsic parameters of an MCS are needed to be calibrated before it is used. / Secondly, we proposed to solve the calibration of a particular model of non-rigid Multiple Camera System, namely, Articulated Camera System (ACS). In an ACS, the cameras are fixed on articulated arms with joints, the relative pose between them may change. Two ACS calibration methods are proposed. In the first approach, we assume the cameras have overlapping views. It uses the feature correspondences between the cameras in the ACS. In the second approach, we assume the cameras have no overlapping view. It requires only the ego-motion information of the cameras and can be used for the calibration of the non-overlapping view ACS. In both methods, the ACS is assumed to have performed general transformations in a static environment. / Chen, Junzhou. / Adviser: Kin Hong Wong. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3594. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 102-110). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_344312 |
| Date | January 2008 |
| Contributors | Chen, Junzhou., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, theses |
| Format | electronic resource, microform, microfiche, 1 online resource (xvii, 110 leaves : ill.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
Page generated in 0.0018 seconds