A method for the automatic reconstruction of 3D objects from multiple camera views for 3D multimedia applications is presented. Conventional 3D reconstruction techniques use equipment that restrict the flexibility of the user. In order to increase this flexibility, the presented method is characterized by a simple measurement environment, that consists of a new calibration pattern placed below the object allowing object and pattern acquisition simultaneously. This ensures, that each view can be calibrated individually. From these obtained calibrated camera views, a textured 3D wireframe model is estimated using a shape--from--silhouette approach and texture mapping of the original camera views. Experiments with this system have confirmed a significant gain of flexibility for the user and a drastic reduction of costs for technical equipment while ensuring comparable model quality as conventional reconstruction techniques at the same time. 1 Introduction Natural looking 3D models of re...

An algorithm for the fast automatic construction of a 3D model of any real object using images from multiple views is presented. The images are taken from a real object rotating in front of a stationary calibrated CCD TV camera. The presented algorithm generates the object shape in a first step. For that purpose an effective implementation of the method of occluding contours is used to obtain a convex volume model of the object. This model is refined in order to detect shape concavities by using additional depth information from disparity estimation and finally approximated by a triangle mesh. In a second step the texture is estimated from the image sequence and projected onto the surface model to obtain natural looking models. Results with real image sequences have confirmed the suitability of the developed algorithm even for the modelling of real objects with highly detailed and complex surfaces. 1 Introduction The objective of this work is the development and refinement of algorith...

This paper presents an overview of a planned system for automatic population of geospatial databases which represent urban exteriors as textured geometric model data. The salient features of the system are that 1) it employs "poseimagery: " high-quality, digital still images, each timestamped, and annotated with a reliable estimate of the acquiring camera's absolute position and attitude; 2) it exploits both dense and sparse image features by sifting evidence for interpixel correlation across every image; 3) it addresses the combinatorial aspects of large-scale 3D reconstruction from thousands of arbitrary images; and 4) it has no "human in the loop." This work involves both engineering and research challenges. The engineering challenges include rapid acquisition of 6-DOF poseinstrumented, high-resolution imagery, and its insertion into a hierarchical three-dimensional data structure. The research challenges include dense reconstruction techniques using thousands of images, and the inc...

An algorithm for the mapping of texture from multiple camera views onto a 3D model of a real object is presented. The texture sources are images taken from an object rotating in front of a stationary calibrated camera. The 3D model is represented by a wireframe built of triangles and is geometrically adjusted to the camera views. The presented approach aims at the reduction of texture distortion associated with the boundaries between triangles mapped from different camera views and disturbance due to not visible parts of the object surface. For this purpose adjacent triangles describing the surface of the 3D model are grouped to homogenous surface regions which are textured with a common image followed by a local texture filtering at the region boundaries. For triangles not visible in any camera view a filter has been developed which uses the texture from adjacent visible triangles for the generation of synthetic texture. Experimental investigations with different real 3D objects have ...

This paper is about multi-view modeling of a rigid scene. We merge the tra- ditional approaches of reconstructing image-extractable features and of modeling via user-provided geometry. We use features to obtain a first guess for structure and motion, fit geometric primitives, correct the structure so that reconstructed fea- tures lie exactly on geometric primitives and optimize both structure and motion in a bundle adjustment manner while enforcing the underlying constraints. We specialize this general scheme to the point features and the plane geometric prim- itives. The underlying geometric relationships are described by multi-coplanarity constraints. We propose a minimal parameterization of the structure enforcing these constraints and use it to devise the corresponding maximum likelihood es- timator. The recovered primitives are then textured from the input images. The result is an accurate and photorealistic model.

Traces" is an immersive art project which uses the CAVE stereo-immersive environment for an unorthodox purpose. While most virtual worlds are based on a paradigm of virtual navigation through texture mapped worlds, Traces has no \world" and no navigation. The aesthetic/theoretical goal of Traces is to focus the attention of the user onto their sense their own of embodiment through time. The bodily behavior of the user generates real-time graphics and sound. The technical goal of Traces is wireless full body interaction without the use of standard trackers, joysticks and wands, and without icons, menus or graphical pointers of any kind. To achieve these goals, we have built an infra-red multi-camera machine-vision system which constructs a volumetric body model of the user in real time. We use this body model data to perform all sensing functions in the CAVE. It controls all graphical and sound events, it replaces the wand or joystick for control, it replaces trackers and supplies tra...

This paper presents an octree based method of three-dimensional reconstruction of objects using a combination of two different methods, Shape from Silhouette and Shape from Structured Light, focusing on reconstruction of archaeological vessels. Shape from Silhouette is a method suitable for reconstruction of objects with handles, whereas it is unable to reconstruct concavities on an object's surface, such as inside of a bowl. Shape from Structured Light can reconstruct such concavities, but it often creates incomplete models because of camera and light occlusions. The purpose of combining these two methods is to overcome the weaknesses of one method through the strengths of the other, making it possible to construct complete models of arbitrarily shaped objects. The construction is based on multiple views of an object using a turntable in front of stationary cameras. Results of the algorithm developed are presented for both synthetic and real objects.

This paper presents a method for converting the contours of a rotated object's profiles into a volumetric object description that is suitable for an integration of complementary visual shape cues. In contrast to traditional shape from contours algorithms, the method presented in this paper does not attempt to construct an 'optimum' solution but rather finds an enclosing volume which must contain the true solution. In this way, an infinite set of solutions is compactly represented which is compatible with the contours in all available views. In the experimental set-up, the object is recorded from multiple viewing angles with a fixed camera. The recorded frames then pass a segmentation step which is carefully designed so that the true object volume will lie inside the reconstructed enclosing volume. The resulting segments are integrated into a voxel based description of the enclosing volume. For illustration purposes, the procedure is tested on a few general objects such as both a hum...

Previous algorithms for recovering 3D geometry from an uncalibrated image sequence of a single axis motion of unknown rotation angles are mainly based on the computation of two-view fundamental matrices and three-view trifocal tensors. In this paper, we propose three new methods that are based on fitting a conic locus to corresponding image points over multiple views. The main advantage is that determining only five parameters of a conic from one corresponding point over at least five views is simpler and more robust than determining a fundamental matrix from two views or a trifocal tensor from three views. It is shown that the geometry of single axis motion can be recovered either by computing one conic locus and one fundamental matrix or by computing at least two conic loci. A maximum likelihood solution based on this parametrization of the single axis motion is also described for optimal estimation using three or more loci. The experiments on real image sequences demonstrate the simplicity, accuracy, and robustness of the new methods.

In this paper we present a voxel-based 3D reconstruction technique to compute photo realistic volume models from multiple color images. Visibility information is the key requirement for photorealistic reconstructions. In order to get the full visibility information item buffers are created for each image. In the item buffers each pixel is assigned the ID of the closest voxel it corresponds to. All scene points are projected into every image and if the ID stored in the pixel is the same as the voxel’s ID, they are checked for photo consistency. This way only visible (non-occluded) voxels are considered. Voxels are labelled either opaque and assigned a color value or transparent and carved away until no non-photo consistent voxel exists. Due to the missing of control points on the object, the images undergo a process of relative orientation in a free network using manually measured tie points. With these image orientations and a previously calibrated camera, the scene points are projected in a high accurate way, minimizing projection errors. This way objects are modelled where the application of control points is either impossible (e.g. in microscopic images) or uneconomical. Experimental results show that the combination of photogrammetric methods and shape from photo consistency techniques yield more accurate results since camera errors are taken into consideration and images are assigned individual orientation data.