Improving the reliability of a GPS/INS navigation solution for MM vehicles by photogrammetry

none3N. E. Cazzaniga; G. Forlani; R. RoncellaCazzaniga, NOEMI EMANUELA; G., Forlani; R., Roncell

Image Based Rendering Using Algebraic Techniques

This paper presents an image-based rendering system using algebraic relations between different views of an object. The system uses pictures of an object taken from known positions. Given three such images it can generate "virtual'' ones as the object would look from any position near the ones that the two input images were taken from. The extrapolation from the example images can be up to about 60 degrees of rotation. The system is based on the trilinear constraints that bind any three view so fan object. As a side result, we propose two new methods for camera calibration. We developed and used one of them. We implemented the system and tested it on real images of objects and faces. We also show experimentally that even when only two images taken from unknown positions are given, the system can be used to render the object from other view points as long as we have a good estimate of the internal parameters of the camera used and we are able to find good correspondence between the example images. In addition, we present the relation between these algebraic constraints and a factorization method for shape and motion estimation. As a result we propose a method for motion estimation in the special case of orthographic projection

Multiple-View Scenes: Reconstruction and Virtual Views

The problem of generating a virtual view of a scene, i.e. a view from a point where there is not a physical camera to capture the scene, has received recently a lot of attention from the computer vision community. This is probably due to the increase of the computational power of computers, which allows to deal with multiple view systems (systems composed of multiple cameras) efficiently. In this document, an introduction to virtual view generation techniques is presented. In a first part, geometric constraints of multiple view systems are presented. This geometric constraints allow to reconstruct the 3D information of the observed scene, and therefore they allow to generate virtual views from everywhere (although problems with occlusions will arise). In the second part of the document, the state-of-the-art on Image Based Rendering (IBR) techniques is presented. IBR techniques allow to generate virtual views from some constrained regions of the space without requiring a complete 3D reconstruction of the scene. To finish, some concussions are given

Multiple-View Scenes: Reconstruction and Virtual Views

The problem of generating a virtual view of a scene, i.e. a view from a point where there is not a physical camera to capture the scene, has received recently a lot of attention from the computer vision community. This is probably due to the increase of the computational power of computers, which allows to deal with multiple view systems (systems composed of multiple cameras) efficiently. In this document, an introduction to virtual view generation techniques is presented. In a first part, geometric constraints of multiple view systems are presented. This geometric constraints allow to reconstruct the 3D information of the observed scene, and therefore they allow to generate virtual views from everywhere (although problems with occlusions will arise). In the second part of the document, the state-of-the-art on Image Based Rendering (IBR) techniques is presented. IBR techniques allow to generate virtual views from some constrained regions of the space without requiring a complete 3D reconstruction of the scene. To finish, some concussions are given

Image based rendering using algebraic techniques

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (p. 55-57).by Theodoros Kostantinos.M.Eng

3D model reconstruction with noise filtering using boundary edges.

Lau Tak Fu.Thesis submitted in: October 2003.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 93-98).Abstracts in English and Chinese.Chapter 1 - --- Introduction --- p.9Chapter 1.1 --- Scope of the work --- p.9Chapter 1.2 --- Main contribution --- p.11Chapter 1.3 --- Outline of the thesis --- p.12Chapter 2 - --- Background --- p.14Chapter 2.1 --- Three dimensional models from images --- p.14Chapter 2.2 --- Un-calibrated 3D reconstruction --- p.14Chapter 2.3 --- Self calibrated 3D reconstruction --- p.16Chapter 2.4 --- Initial model formation using image based --- p.18Chapter 2.5 --- Volumes from Silhouettes --- p.19Chapter 3 - --- Initial model reconstruct the problem with mismatch noise --- p.22Chapter 3.1 --- Perspective Camera Model --- p.24Chapter 3.2 --- "Intrinsic parameters, Extrinsic parameters and camera motion" --- p.25Chapter 3.2.1 --- Intrinsic parameters --- p.25Chapter 3.2.2 --- Extrinsic parameter and camera motion --- p.27Chapter 3.3 --- Lowe's method --- p.29Chapter 3.4 --- Interleave bundle adjustment for structure and motion recovery from multiple images --- p.32Chapter 3.5 --- Feature points mismatch analysis --- p.38Chapter 4 - --- Feature selection by using look forward silhouette clipping --- p.43Chapter 4.1 --- Introduction to silhouette clipping --- p.43Chapter 4.2 --- Silhouette clipping for 3D model --- p.45Chapter 4.3 --- Implementation --- p.52Chapter 4.3.1 --- Silhouette extraction program --- p.52Chapter 4.3.2 --- Feature filter for alternative bundle adjustment algorithm --- p.59Chapter 5 - --- Experimental data --- p.61Chapter 5.1 --- Simulation --- p.61Chapter 5.1.1 --- Input of simulation --- p.61Chapter 5.1.2 --- Output of the simulation --- p.66Chapter 5.1.2.1 --- Radius distribution --- p.66Chapter 5.1.2.2 --- 3D model output --- p.74Chapter 5.1.2.3 --- VRML plotting --- p.80Chapter 5.2 --- Real Image testing --- p.82Chapter 5.2.1 --- Toy house on a turntable test --- p.82Chapter 5.2.2 --- Other tests on turntable --- p.86Chapter 6 - --- Conclusion and discussion --- p.8

Automatic visual recognition using parallel machines

Invariant features and quick matching algorithms are two major concerns in the area of automatic visual recognition. The former reduces the size of an established model database, and the latter shortens the computation time. This dissertation, will discussed both line invariants under perspective projection and parallel implementation of a dynamic programming technique for shape recognition. The feasibility of using parallel machines can be demonstrated through the dramatically reduced time complexity. In this dissertation, our algorithms are implemented on the AP1000 MIMD parallel machines. For processing an object with a features, the time complexity of the proposed parallel algorithm is O(n), while that of a uniprocessor is O(n2). The two applications, one for shape matching and the other for chain-code extraction, are used in order to demonstrate the usefulness of our methods. Invariants from four general lines under perspective projection are also discussed in here. In contrast to the approach which uses the epipolar geometry, we investigate the invariants under isotropy subgroups. Theoretically speaking, two independent invariants can be found for four general lines in 3D space. In practice, we show how to obtain these two invariants from the projective images of four general lines without the need of camera calibration. A projective invariant recognition system based on a hypothesis-generation-testing scheme is run on the hypercube parallel architecture. Object recognition is achieved by matching the scene projective invariants to the model projective invariants, called transfer. Then a hypothesis-generation-testing scheme is implemented on the hypercube parallel architecture