Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography Vol. 32, No. 3, 205-216, 2014 http://dx.doi.org/10.7848/ksgpc.2014.32.3.205 Multi-camera System Calibration with Built-in Relative Orientation Constraints (Part 2) Automation, Implementation, and Experimental Results Lari, Zahra 1) · Habib, Ayman 2) · Mazaheri, Mehdi 3) · Al-Durgham, Kaleel 4) Abstract Multi-camera systems have been widely used as cost-effective tools for the collection of geospatial data for various applications. In order to fully achieve the potential accuracy of these systems for object space reconstruction, careful system calibration should be carried out prior to data collection. Since the structural integrity of the involved cameras’ components and system mounting parameters cannot be guaranteed over time, multi-camera system should be frequently calibrated to confirm the stability of the estimated parameters. Therefore, automated techniques are needed to facilitate and speed up the system calibration procedure. The automation of the multi-camera system calibration approach, which was proposed in the first part of this paper, is contingent on the automated detection, localization, and identification of the object space signalized targets in the images. In this paper, the automation of the proposed camera calibration procedure through automatic target extraction and labelling approaches will be presented. The introduced automated system calibration procedure is then implemented for a newly-developed multi-camera system while considering the optimum configuration for the data collection. Experimental results from the implemented system calibration procedure are finally presented to verify the feasibility the proposed automated procedure. Qualitative and quantitative evaluation of the estimated system calibration parameters from two-calibration sessions is also presented to confirm the stability of the cameras’ interior orientation and system mounting parameters. Keywords : Multi-camera system, Calibration, Automation, Coded targets, Checkerboard targets, System configuration 205 ISSN 1598-4850(Print) ISSN 2288-260X(Online) Original article Received 2014. 03. 13, Revised 2014. 04. 08, Accepted 2014. 05. 29 1) Corresponding Author·Department of Geomatics Engineering, University of Calgary(Email: zlari@ucalgary.ca) 2) Department of Geomatics Engineering, University of Calgary(Email: ahabib@ucalgary.ca) 3) Department of Geomatics Engineering, University of Calgary(Email: m.mazaheri@ucalgary.ca) 4) Department of Geomatics Engineering, University of Calgary(Email: kaldurgham@ucalgary.ca) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction In recent years, multi-camera systems have gained more popularity due to their ability in quickly and economically collecting geospatial data. These systems include multiple integrated low-cost cameras mounted on a kinematic or static platform. The multi-camera systems can be used for different mapping, modelling, and 3D surface reconstruction applications. In order to achieve the desired accuracy of these systems for the object space reconstruction process, an appropriate system calibration procedure should be performed prior to data collection. The calibration of a multi-camera system is accomplished when the involved cameras in the system are calibrated and the mounting parameters relating the different system components are estimated (Habib et al., 2011; Rau et al., 2011). Multi-camera systems usually involve low-cost digital cameras, where the structural integrity of their components cannot be guaranteed. Moreover, the stability of the system mounting parameters might change over time. Therefore, the system calibration should be frequently performed to confirm the stability of the cameras’ Interior Orientation Parameters (IOPs) and the system