2023 |
Verykokou, Styliani; Ioannidis, Charalabos An Overview on Image-Based and Scanner-Based 3D Modeling Technologies Journal Article In: Sensors, vol. 23, no. 2, pp. 596, 2023, ISSN: 1424-8220. Abstract | Links | BibTeX | Tags: 3D modeling, CBCT, CMM, CT, laser scanners, MRI, multi-view stereo, scanners, segmentation, structure from motion @article{verykokou2023overview,Advances in the scientific fields of photogrammetry and computer vision have led to the development of automated multi-image methods that solve the problem of 3D reconstruction. Simultaneously, 3D scanners have become a common source of data acquisition for 3D modeling of real objects/scenes/human bodies. This article presents a comprehensive overview of different 3D modeling technologies that may be used to generate 3D reconstructions of outer or inner surfaces of different kinds of targets. In this context, it covers the topics of 3D modeling using images via different methods, it provides a detailed classification of 3D scanners by additionally presenting the basic operating principles of each type of scanner, and it discusses the problem of generating 3D models from scans. Finally, it outlines some applications of 3D modeling, beyond well-established topographic ones. |
2020 |
Verykokou, Styliani; Ioannidis, Charalabos Exterior orientation estimation of oblique aerial images using SfM-based robust bundle adjustment Journal Article In: Int. J. Remote Sens., vol. 41, no. 18, pp. 7233–7270, 2020, ISSN: 0143-1161. Abstract | Links | BibTeX | Tags: aerial triangulation, exterior orientation, oblique aerial images, Photogrammetry, structure from motion @article{Verykokou2020,In this article, a structure from motion (SfM) framework for oblique aerial images of man-made environments is proposed, covering the issues of determining overlapping images, feature extraction, image matching, rejection of erroneous correspondences, feature tracking, automatic transfer of ground control points (GCPs), and bundle block adjustment. One of the challenges that it is intended to solve is the reduction of the required manual work concerning the measurement of GCPs, in order to increase the degree of automation of the exterior orientation estimation process, through the usage of geometric constraints automatically imposed. Yet another challenge is the difficulty in matching correctly feature points among multiple oblique views that depict scenes with repetitive patterns and homogeneous textures. The proposed algorithm solves this by eliminating all erroneous tie points through the combination of multiple checks and geometric constraints imposed during the image matching procedure and a robust iterative bundle adjustment framework. The proposed SfM methodology is applied in different configurations of oblique images under non-ideal aerial triangulation scenarios characterized by lack of well-distributed GCPs as well as minimum manual image measurements. The results are analysed, focusing on the improvement of the accuracy of the exterior orientation parameters thanks to the proposed robust out-lier removal technique as well as on the impact of the proposed scale-based weighting strategy for bundle adjustment of oblique images on the exterior orientation results. The proposed SfM framework proves to be a good alternative solution to existing commercial SfM methods. ARTICLE HISTORY |
2018 |
Verykokou, Styliani; Ioannidis, Charalabos A PHOTOGRAMMETRY-BASED STRUCTURE FROM MOTION ALGORITHM USING ROBUST ITERATIVE BUNDLE ADJUSTMENT TECHNIQUES Journal Article In: ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci., vol. IV-4/W6, pp. 73–80, 2018, ISSN: 2194-9050. Abstract | Links | BibTeX | Tags: Bundle Adjustment, Coplanar Feature Points, exterior orientation, Homography, Oblique Images, structure from motion, Template Matching @article{Verykokou2018,Abstract. The purpose of this paper is the presentation of a novel algorithm for automatic estimation of the exterior orientation parameters of image datasets, which can be applied in the case that the scene depicted in the images has a planar surface (e.g., roof of a building). The algorithm requires the measurement of four coplanar ground control points (GCPs) in only one image. It uses a template matching method combined with a homography-based technique for transfer of the GCPs in another image, along with an incremental photogrammetry-based Structure from Motion (SfM) workflow, coupled with robust iterative bundle adjustment methods that reject any remaining outliers, which have passed through the checks and geometric constraints imposed during the image matching procedure. Its main steps consist of (i) determination of overlapping images without the need for GPS/INS data; (ii) image matching and feature tracking; (iii) estimation of the exterior orientation parameters of a starting image pair; and (iv) photogrammetry-based SfM combined with iterative bundle adjustment methods. A developed software solution implementing the proposed algorithm was tested using a set of UAV oblique images. Several tests were performed for the assessment of the errors and comparisons with well-established commercial software were made, in terms of automation and correctness of the computed exterior orientation parameters. The results show that the estimated orientation parameters via the proposed solution have comparable accuracy with those ones computed through the commercial software using the highest possible accuracy settings; in addition, double manual work was required by the commercial software compared to the proposed solution. |
2016 |
Georgopoulos, A; Oikonomou, C; Adamopoulos, E; Stathopoulou, E K EVALUATING UNMANNED AERIAL PLATFORMS FOR CULTURAL HERITAGE LARGE SCALE MAPPING Journal Article In: ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., vol. XLI-B5, pp. 355–362, 2016, ISSN: 2194-9034. Abstract | Links | BibTeX | Tags: dense matching, large scale mapping, orthophotos, structure from motion, UAS @article{Georgopoulos2016,When it comes to large scale mapping of limited areas especially for cultural heritage sites, things become critical. Optical and non-optical sensors are developed to such sizes and weights that can be lifted by such platforms, like e.g. LiDAR units. At the same time there is an increase in emphasis on solutions that enable users to get access to 3D information faster and cheaper. Considering the multitude of platforms, cameras and the advancement of algorithms in conjunction with the increase of available computing power this challenge should and indeed is further investigated. In this paper a short review of the UAS technologies today is attempted. A discussion follows as to their applicability and advantages, depending on their specifications, which vary immensely. The on-board cameras available are also compared and evaluated for large scale mapping. Furthermore a thorough analysis, review and experimentation with different software implementations of Structure from Motion and Multiple View Stereo algorithms, able to process such dense and mostly unordered sequence of digital images is also conducted and presented. As test data set, we use a rich optical and thermal data set from both fixed wing and multi-rotor platforms over an archaeological excavation with adverse height variations and using different cameras. Dense 3D point clouds, digital terrain models and orthophotos have been produced and evaluated for their radiometric as well as metric qualities. |
2023 |
An Overview on Image-Based and Scanner-Based 3D Modeling Technologies Journal Article In: Sensors, vol. 23, no. 2, pp. 596, 2023, ISSN: 1424-8220. |
2020 |
Exterior orientation estimation of oblique aerial images using SfM-based robust bundle adjustment Journal Article In: Int. J. Remote Sens., vol. 41, no. 18, pp. 7233–7270, 2020, ISSN: 0143-1161. |
2018 |
A PHOTOGRAMMETRY-BASED STRUCTURE FROM MOTION ALGORITHM USING ROBUST ITERATIVE BUNDLE ADJUSTMENT TECHNIQUES Journal Article In: ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci., vol. IV-4/W6, pp. 73–80, 2018, ISSN: 2194-9050. |
2016 |
EVALUATING UNMANNED AERIAL PLATFORMS FOR CULTURAL HERITAGE LARGE SCALE MAPPING Journal Article In: ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., vol. XLI-B5, pp. 355–362, 2016, ISSN: 2194-9034. |