Stoltz, George G2019-10-292019-10-292019-01Stoltz, G.G. 2019. Image stitching for usage in photogrammetric algorithms. 2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA 2019), Bloemfontein, South Africa, 28-30 January 2019, pp 129-134978-1-7281-0369-3978-1-7281-0370-9http://toc.proceedings.com/48648webtoc.pdfhttps://ieeexplore.ieee.org/document/8704814DOI: 10.1109/RoboMech.2019.8704814http://hdl.handle.net/10204/11197Copyright: 2019 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, kindly consult the publisher's websiteA distributed camera system can consist of multiple camera groups. An image stitch is created by each group and transmitted to a central processing unit. The central processing combines all received images into an image stitch. The camera groups can have cameras with large overlapping areas and transmitting a stitched image will reduce the required bandwidth. Unfortunately, photogrammetric algorithms such as stitching, assume images adhere to the pinhole camera model. Thus, photogrammetric algorithms cannot be applied to image stitches created by currently available grid generation techniques. In this paper a grid generation method to create a stitched image with the properties of a pinhole camera is presented. The method is evaluated by simulating eight cameras, forming two groups, each group covering a quarter-hemisphere. The intrinsic and extrinsic parameters of each camera is known. A groundtruth is created by a spherical stitch of all eight cameras covering the half-hemisphere. To test, each camera group is stitched using the pinhole camera transformation. The transformation produce artificial intrinsic and extrinsic parameters for each stitch. A half-hemisphere spherical stitch is created using the two camera group stitches, each with their relative intrinsic and extrinsic parameters. The half-hemisphere stitch is compared to the groundtruth, producing almost perfect correlation. The high correlation indicates the success of the pinhole camera transformation. The pinhole camera transformation enable the usage of stitched images in photogrammetric algorithms.enPhotogrammetric algorithmsHomographyPinhole cameraMachine visionPhotogrammetryConference PresentationStoltz, G. G. (2019). Image stitching for usage in photogrammetric algorithms. IEEE. http://hdl.handle.net/10204/11197Stoltz, George G. "Image stitching for usage in photogrammetric algorithms." (2019): http://hdl.handle.net/10204/11197Stoltz GG, Image stitching for usage in photogrammetric algorithms; IEEE; 2019. http://hdl.handle.net/10204/11197 .TY - Conference Presentation AU - Stoltz, George G AB - A distributed camera system can consist of multiple camera groups. An image stitch is created by each group and transmitted to a central processing unit. The central processing combines all received images into an image stitch. The camera groups can have cameras with large overlapping areas and transmitting a stitched image will reduce the required bandwidth. Unfortunately, photogrammetric algorithms such as stitching, assume images adhere to the pinhole camera model. Thus, photogrammetric algorithms cannot be applied to image stitches created by currently available grid generation techniques. In this paper a grid generation method to create a stitched image with the properties of a pinhole camera is presented. The method is evaluated by simulating eight cameras, forming two groups, each group covering a quarter-hemisphere. The intrinsic and extrinsic parameters of each camera is known. A groundtruth is created by a spherical stitch of all eight cameras covering the half-hemisphere. To test, each camera group is stitched using the pinhole camera transformation. The transformation produce artificial intrinsic and extrinsic parameters for each stitch. A half-hemisphere spherical stitch is created using the two camera group stitches, each with their relative intrinsic and extrinsic parameters. The half-hemisphere stitch is compared to the groundtruth, producing almost perfect correlation. The high correlation indicates the success of the pinhole camera transformation. The pinhole camera transformation enable the usage of stitched images in photogrammetric algorithms. DA - 2019-01 DB - ResearchSpace DP - CSIR KW - Photogrammetric algorithms KW - Homography KW - Pinhole camera KW - Machine vision KW - Photogrammetry LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-7281-0369-3 SM - 978-1-7281-0370-9 T1 - Image stitching for usage in photogrammetric algorithms TI - Image stitching for usage in photogrammetric algorithms UR - http://hdl.handle.net/10204/11197 ER -