| Titre : |
Image-based modeling for object and human reconstruction |
| Type de document : |
Thèse/HDR |
| Auteurs : |
Fabio Remondino, Auteur |
| Editeur : |
Zurich : Institut für Geodäsie und Photogrammetrie IGP - ETH |
| Année de publication : |
2006 |
| Collection : |
IGP Mitteilungen, ISSN 0252-9335 num. 091  |
| Importance : |
159 p. |
| Format : |
21 x 30 cm |
| ISBN/ISSN/EAN : |
978-3-906467-61-0 |
| Note générale : |
Bibliographie |
| Langues : |
Anglais (eng) |
| Descripteur : |
[Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] acquisition d'images
[Termes IGN] compensation par faisceaux
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] extraction automatique
[Termes IGN] géométrie projective
[Termes IGN] modélisation 3D
[Termes IGN] objet mobile
[Termes IGN] orientation du capteur
[Termes IGN] orientation externe
[Termes IGN] orientation interne
[Termes IGN] orientation relative
[Termes IGN] photogrammétrie terrestre
[Termes IGN] points homologues
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] traitement d'image
[Termes IGN] vision par ordinateur
|
| Index. décimale : |
33.30 Photogrammétrie numérique |
| Résumé : |
(Auteur) The topic of this research is the investigation of the image-based approach for the 3D modeling of close-range scenes, static objects and moving human characters. Three-dimensional (3D) modeling from images is a great topic of investigation in the research community, even if range sensors are becoming more and more a common source and a good alternative for the generation of 3D information. The interest in 3D modeling is motivated by a wide spectrum of applications, such as video games, animation, navigation of autonomous vehicles, object recognition, surveillance and visualization. In particular, the production of 3D models from existing images or old movies would allow the generation of new scenes involving objects or human characters who may be unavailable for other modeling techniques.
Techniques for 3D modeling have been rapidly advancing over the past few years although most of them focus on single objects or specific applications such as architecture or city mapping. Nowadays the accurate and fully automated reconstruction of 3D models from image data is still a challenging problem. Most of the current approaches developed to recover accurate 3D models are based on semi-automatic procedures, therefore the introduction of new reliable and automated algorithms is one of the key goals in the photogrammetric and vision communities. In fact fully automated image-based approaches generally do not work under certain image network configuration or are not reliable enough for some applications, like cultural heritage documentation. Automated image-based methods require good features in multiple images and very short baselines between consecutive frames to extract dense depth maps and complete 3D models. But these requirements are not satisfied in some practical situations, due to occlusions, illumination changes and lack of texture. Automated processes often end up with areas containing too many features that are not all needed for the object modeling and areas with very few features to pro-duce a complete and detailed model. Automated reconstruction methods generally do not report good accuracy, limiting their use for applications that require only nice-looking 3D models. Furthermore, post processing operations are often required, which means that the user interaction is still needed. Therefore fully automated procedures are generally limited in finding point correspondences and camera poses while for the surface measurement phase the user interaction is generally preferred, in particular for architectures.
The image-based modeling of an object should be meant as the complete process that starts from the acquisition system and ends with a virtual model in three dimensions visible interactively on a computer. The photogrammetric modeling pipeline consists of few well known steps: calibration and orientation, surface measurement and point cloud generation, structuring and modeling of the object geometry, visualization and analysis. Different efforts have been done to increase the level of automation within these steps and broaden the use of the image-based modeling technology. So far, however, the efforts to completely automate the processing, from the image acquisition to the output of a 3D model, are not always successful or not applicable in many 3D modeling projects.
In this dissertation different techniques developed to analyze existing sequence of images and partially automate the process of constructing digital 3D models of static objects or moving human characters are reported. In particular the work investigates if automated and markerless sensor orientation is feasible and under which conditions, if it is possible to recover complete and detailed 3D models of complex objects using automated measurement procedures, which kind of (3D) information can be retrieved from existing image data as well as the capabilities or limits of photogrammetric algorithms in dealing with uncalibrated images and zooming effects. For the investigations, sets of available or self-acquired images, as well as frames digitized from existing monocular videos are used.
The possibility to automatically orient an image sequence heavily depends on the type of images, acquisition and scene. Compared to other research approaches, the developed method for the automated tie point extraction and image orientation relies on accurate feature location achieved using least squares matching measurement algorithm and a statistical analysis of the matched and adjustment results. The reported examples demonstrate its capabilities also for the orientation of images acquired under a wide baseline. A photogrammetric bundle adjustment is always employed to recover the camera parameters and the 3D object coordinates. On the other hand, the analysis of moving human characters using a monocular video is based on a deterministic approach together with constraints and assumptions on the imaged scene as well as on the human's shape and movement. The developed photogrammetric pipeline can accommodate different input data and different types of human motions. The resulted 3D characters and scene information can be used for visualization or animation purposes or in biometric applications with medium accuracy requirements.
For the automated tie point extraction phase, programs for the feature extraction and the relative orientation between image pairs and triplets were implemented, together with a graphical tool to display the recovered correspondences and epipolar geometry. Concerning the human reconstruction from monocular videos, programs were developed to recover 3D models from single images and combine them under the same reference system in case of image sequence analysis. |
| Note de contenu : |
1. INTRODUCTION
1.1. 3D Modeling
1.2. Motivations, objectives and contributions
1.3. Overview and organization
2. PROJECTIVE GEOMETRY
2.1. Geometry layers
2.2. Homogeneous coordinates: points, lines, planes and conies
2.3. Projective transformation
2.4. Projective invariants
2.5. Projective camera model
2.6. The reconstruction problem
3. 3D MODELING FROM IMAGES
3.1. 3D modeling overview
3.2. Terrestrial image-based 3D modeling
3.3. 3D modeling from a single image
3.4. Examples
3.5. Final considerations
4. CALIBRATION AND ORIENTATION OF IMAGE SEQUENCES
4.1. Orientation approaches
4.2. Automated tie point extraction
4.3. Bundle adjustment
4.4. Approximative values for the adjustment's unknowns
4.5. Linear features bundle adjustment
4.6. Calibration and orientation of stationary but freely rotating cameras
4.7. Calibration of stationary and fixed camera
5. HUMAN BODY MODELING AND MOVEMENT RECONSTRUCTION
5.1. 3D Modeling of human characters
5.2. Image-based reconstruction of static human body shape
5.3. Forensic metrology
5.4. Markerless motion capture from monocular videos
6. EXPERIMENTS
6.1. Automated markerless tie point extraction
6.2. 3D modeling of an architectural object
6.3. Human body shape modeling from images
6.4. Photogrammetric analysis of monocular videos
6.5. Cultural Heritage object modeling
7. CONCLUSIONS
7.1. Summary of the achievements
7.2. Automated markerless image orientation
7.3. 3D models from images
7.4. Human character reconstruction
7.5. Future work
Appendix A. Detectors and descriptors
A.1. Operators for photogrammetric applications
A.2. Point and region detectors
A.3. Descriptors
A.4. Experimental setup and results
A.5. Location accuracy improvement for detectors and descriptors
A.6. Conclusions
Appendix B. Alternative form of the coplanarity condition
B.1. Relative orientation between two images
B.2. Estimating the Fundamental matrix
B.2.1. Least squares and iterative techniques
B.2.2. Robust estimators |
| Numéro de notice : |
15201 |
| Affiliation des auteurs : |
non IGN |
| Thématique : |
IMAGERIE |
| Nature : |
Thèse étrangère |
| DOI : |
10.3929/ethz-a-005211924 |
| En ligne : |
http://dx.doi.org/10.3929/ethz-a-005211924 |
| Format de la ressource électronique : |
URL |
| Permalink : |
https://documentation.ensg.eu/index.php?lvl=notice_display&id=55093 |
|  |
Image-based modeling for object and human reconstruction (2006)
