3d Modelling with Linear Approaches Using Geometric Primitives

In this paper, we study linear approaches for 3D model acquisition from non-calibrated images. First, the intrinsic andextrinsic camera calibration is taken into consideration. In particular, we study the use of a specific calibrationprimitive: the parallelepiped. Parallelepipeds are frequently present in man-made environments and naturally encode theaffine structure of the scene. Any information about their euclidean structure (angles or ratios of edge lengths), possiblycombined with information about camera parameters is useful to obtain the euclidean reconstruction. We propose anelegant formalism to incorporate such information, in which camera parameters are dual to parallelepiped parameters,i.e. any knowledge about one entity provides constraints on the parameters of the others. Consequently, an image aparallelepiped with known Euclidean structure allows to compute the intrinsic camera parameters, and reciprocally, acalibrated image of a parallelepiped allows to recover its euclidean shape (up to size). On the conceptual level, thisduality can be seen as an alternative way to understand camera calibration: usually, calibration is considered to beequivalent to localizing the absolute conic or quadric in an image, whereas here we show that other primitives, such ascanonic parallelepipeds, can be used as well. While the main contributions of this work concern the estimation ofcamera and parallelepiped parameters. The complete system allows both calibration and 3D model acquisition from asmall number of arbitrary images with a reasonable amount of user interaction

Using Geometric Constraints for Camera Calibration and Positioning and 3D Scene Modelling

International audienceThis work concerns the incorporation of geometric information in camera calibration and 3D modelling. Using geometric constraints enables stabler results and allows to perform tasks with fewer images. Our approach is interactive; the user defines geometric primitives and constraints between them. It is based on the observation that constraints such as coplanarity, parallelism or orthogonality, are easy to delineate by a user, and are well adapted to model the main structure of e.g. architectural scenes. We propose methods for camera calibration, camera position estimation and 3D scene reconstruction, all based on such geometric constraints. Various approaches exist for calibration and positioning from constraints, often based on vanishing points. We generalize this by considering composite primitives based on triplets of vanishing points. These are frequent in architectural scenes and considering composites of vanishing points makes computations more stable. They are defined by depicting in the images points belonging to parallelepipedic structures (e.g. appropriate points on two connected walls). Constraints on angles or length ratios on these structures can then be easily imposed. A method is proposed that "collects" all these data for all considered images, and computes simultaneously the calibration and pose of all cameras via matrix factorization. 3D scene reconstruction is then performed using many more geometric constraints, i.e. not only those encapsulated by parallelepipedic structures. A method is proposed that reconstructs the whole scene in iterations, solving a linear equation system at each iteration, and which includes an analysis of the parts of the scene that can/cannot be reconstructed at the current stage. The complete approach is validated by various experimental results, for cases where a single or several views are available

3D MODELLING WITH LINEAR APPROACHES USING GEOMETRIC PRIMITIVES

In this paper, we study linear approaches for 3D model acquisition from non-calibrated images. First, the intrinsic andextrinsic camera calibration is taken into consideration. In particular, we study the use of a specific calibrationprimitive: the parallelepiped. Parallelepipeds are frequently present in man-made environments and naturally encode theaffine structure of the scene. Any information about their euclidean structure (angles or ratios of edge lengths), possiblycombined with information about camera parameters is useful to obtain the euclidean reconstruction. We propose anelegant formalism to incorporate such information, in which camera parameters are dual to parallelepiped parameters,i.e. any knowledge about one entity provides constraints on the parameters of the others. Consequently, an image aparallelepiped with known Euclidean structure allows to compute the intrinsic camera parameters, and reciprocally, acalibrated image of a parallelepiped allows to recover its euclidean shape (up to size). On the conceptual level, thisduality can be seen as an alternative way to understand camera calibration: usually, calibration is considered to beequivalent to localizing the absolute conic or quadric in an image, whereas here we show that other primitives, such ascanonic parallelepipeds, can be used as well. While the main contributions of this work concern the estimation ofcamera and parallelepiped parameters. The complete system allows both calibration and 3D model acquisition from asmall number of arbitrary images with a reasonable amount of user interaction.Keywords: parallelepiped, the affine structure, euclidean structure, 3D mode

Architectural Scene Reconstruction from Single or Multiple Uncalibrated Images

In this paper we present a system for the reconstruction of 3D models of architectural scenes from single or multiple uncalibrated images. The partial 3D model of a building is recovered from a single image using geometric constraints such as parallelism and orthogonality, which are likely to be found in most architectural scenes. The approximate corner positions of a building are selected interactively by a user and then further refined automatically using Hough transform. The relative depths of the corner points are calculated according to the perspective projection model. Partial 3D models recovered from different viewpoints are registered to a common coordinate system for integration. The 3D model registration process is carried out using modified ICP (iterative closest point) algorithm with the initial parameters provided by geometric constraints of the building. The integrated 3D model is then fitted with piecewise planar surfaces to generate a more geometrically consistent model. The acquired images are finally mapped onto the surface of the reconstructed 3D model to create a photo-realistic model. A working system which allows a user to interactively build a 3D model of an architectural scene from single or multiple images has been proposed and implemented

3D Volumetric Reconstruction and Characterization of Objects from Uncalibrated Images

Three-dimensional (3D) object reconstruction using only bi-dimensional (2D) images has been a major research topic in Computer Vision. However, it is still a complex problem to solve, when automation, speed and precision are required. In the work presented in this paper, we developed a computational platform with the main purpose of building 3D geometric models from uncalibrated images of objects. Simplicity and automation were our major guidelines to choose volumetric reconstruction methods, such as Generalized Voxel Coloring. This method uses photo-consistency measures to build an accurate 3D geometric model, without imposing any kind of restrictions on the relative motion between the camera used and the object to be reconstructed. Our final goal is to use our computational platform in building and characterize human external anatomical shapes using a single off-the-shelf camera

3D Reconstruction Using a Stereo Vision System with Simplified Inter-Camera Geometry

This thesis addresses the relationship between camera configuration and 3D Euclidean reconstruction. Simulations have been conducted and have shown that when error is present, the larger rotation angle, the worse the reconstruction quality. When rotation is avoided, errors in the intrinsic parameters do not affect the 3D reconstruction in a significant way. Therefore, it is suggested to minimize or avoid rotation when constructing a stereo vision system. Once this configuration is applied, inaccurate intrinsic parameters, even without the prior information of intrinsic parameters, can also yield good reconstruction quality. The configuration of pure translation also provides a framework, which can be used to compute elements of intrinsic parameters with an additional geometry constraint. The perpendicular constraint is selected as an example. Focal length can be recovered from this constraint by assuming the principal point is the centre of the image

Intravital three-dimensional bioprinting

Fabrication of three-dimensional (3D) structures and functional tissues directly in live animals would enable minimally invasive surgical techniques for organ repair or reconstruction. Here, we show that 3D cell-laden photosensitive polymer hydrogels can be bioprinted across and within tissues of live mice, using bio-orthogonal two-photon cycloaddition and crosslinking of the polymers at wavelengths longer than 850 nm. Such intravital 3D bioprinting\u2014which does not create by-products and takes advantage of commonly available multiphoton microscopes for the accurate positioning and orientation of the bioprinted structures into specific anatomical sites\u2014enables the fabrication of complex structures inside tissues of live mice, including the dermis, skeletal muscle and brain. We also show that intravital 3D bioprinting of donor-muscle-derived stem cells under the epimysium of hindlimb muscle in mice leads to the de novo formation of myofibres in the mice. Intravital 3D bioprinting could serve as an in vivo alternative to conventional bioprinting

Intravital three-dimensional bioprinting

Fabrication of three-dimensional (3D) structures and functional tissues directly in live animals would enable minimally invasive surgical techniques for organ repair or reconstruction. Here, we show that 3D cell-laden photosensitive polymer hydrogels can be bioprinted across and within tissues of live mice, using bio-orthogonal two-photon cycloaddition and crosslinking of the polymers at wavelengths longer than 850 nm. Such intravital 3D bioprinting—which does not create by-products and takes advantage of commonly available multiphoton microscopes for the accurate positioning and orientation of the bioprinted structures into specific anatomical sites—enables the fabrication of complex structures inside tissues of live mice, including the dermis, skeletal muscle and brain. We also show that intravital 3D bioprinting of donor-muscle-derived stem cells under the epimysium of hindlimb muscle in mice leads to the de novo formation of myofibres in the mice. Intravital 3D bioprinting could serve as an in vivo alternative to conventional bioprinting

Reconstruction de scènes à partir d'une seule image

National audienceThe human eye, connected with the human mind, is the base tool that allows us to perceive and interpret the world surrounding us. Our eyes let us not only simply see objects- we can recognize forms, follow movements, estimate distanoes and velocities. The computer vision is the discipline, which tries to apply those capabilities to computers. This allows to improve and complete our vision and, on the other hand, to eliminate the need of human interaction in certain applications. The number and importance of applications of computer vision in to- day's world is difficult to underestimate. Surveillance, robotics, assistance in surgical operations and CAD / CAM systems are only some in the wide range of disciplines which are developed mostly thanks to progress in computer vision_ The reasons for applying computer vision are numerous: its flexibility, ability of fast treatment of large amounts of data and, above all, the possibility to exprem information in a clear and intuitive way. One branch of computer vision deals with the extraction of threedimensional information from images. The ability of interpretation of 3D data is necessary in some kinds of applications. Consider for example robotics, the problem of obstacle avoidance, or applications for 3D model visualisation. In this work we are interested in using computer vision to construct threedimensional models of scenes. Reconstruction of geometric models allows us to observe scenes from different points of view. Texture information, which can be extracted from images, permits to obtain photorealistical renderings of models

Digital reconstruction of District Six architecture from archival photographs

Word processed copy.Includes bibliographical references (leaves 88-92).In this thesis we present a strategy for reconstructing instances of District Six Architecture from small sets of old. uncalibrated photographs that are located in the District Six Museum photographic archive. Our reconstruction strategy comprises two major parts. First, we implement a geometry reconstruction framework. based on work by Debevec et al. [1996]. This is used to reconstruct the geometry of a building given as little input as a single photograph. The approach used in this framework requires the user to design a basic model representing the building at hand. using a set of geometric primitives, and then define correspondences between the edges of this model and the edges of the building that are visible in the photographs. This approach is effective, as constraints inherent III the geometry of architectural scenes are exploited through the use of these primitives. The second component of the reconstruction strategy involves texturing the reconstructed models. To accomplish this, we use a combination of the original textures extracted from the photographs, and synthesized textures generated from samples of the original textures. For each face of the reconstructed model, the user is able to use either the original texture material. synthesized material, or a combination of both to create desirable results. Finally, to illustrate the effectiveness of our reconstruction strategy, we consider three example cases of District Six architecture and their reconstructions. All three examples were reconstructed successfully, and using findings from these results, critical analyses of both aspects of our strategy are presented