A number of techniques have been developed for reconstructing surfaces by integrating groups of aligned range images. A desirable set of properties for such algorithms includes: incremental updating, representation of directional uncertainty, the ability to fill gaps in the reconstruction, and robustness in the presence of outliers. Prior algorithms possess subsets of these properties. In this paper, we present a volumetric method for integrating range images that possesses all of these properties. Our volumetric representation consists of a cumulative weighted signed distance function. Working with one range image at a time, we first scan-convert it to a distance function, then combine this with the data already acquired using a simple additive scheme. To achieve space efficiency, we employ a run-length encoding of the volume. To achieve time efficiency, we resample the range image to align with the voxel grid and traverse the range and voxel scanlines synchronously. We generate the f...

We introduce ideas, proposed technologies, and initial results for an office of the future that is based on a unified application of computer vision and computer graphics in a system that combines and builds upon the notions of the CAVE^TM, tiled display systems, and image-based modeling. The basic idea is to use real-time computer vision techniques to dynamically extract per-pixel depth and reflectance information for the visible surfaces in the office including walls, furniture, objects, and people, and then to either project images on the surfaces, render images of the surfaces, or interpret changes in the surfaces. In the first case, one could designate every-day (potentially irregular) real surfaces in the office to be used as spatially immersive display surfaces, and then project high-resolution graphics and text onto those surfaces. In the second case, one could transmit the dynamic image-based models over a network for display at a remote site. Finally, one could interpret dyna...

The 3D Image warping algorithm by McMillan and Bishop uses regular single-layered depth images (which are called reference images) as the initial input. Tears or gaps may appear in the output when the previously occluded areas are exposed in the new viewing position. Many reference images that are taken from different positions can be used to attenuate the occlusion problems but the rendering cost increases with the number of reference images. Also, combining the multiple reference images and eliminating the redundant information is a non-trivial problem. Recently, the Layered Depth Image (LDI) was proposed by Shade et al. to merge multiple reference images under a single center of projection. It tackles the occlusion problems by keeping multiple depth pixels per pixel location, while still maintaining the simplicity of warping a single reference image. However, it does not consider the issue of sampling rate. We present the LDI tree, which combines a hierarchical space partition scheme with the concept of LDI. It preserves the sampling rates of the reference images by adaptively selecting an LDI in the LDI tree for each pixel. While rendering from the LDI tree, we only have to traverse the LDI tree to the levels that are comparable to the sampling rate of the output image. We also present the progressive refinement feature and a "gap filling" algorithm by pre-filtering the LDI tree. We show that the amount of memory required is of the same order as the 2D reference images. This also bounds the complexity of rendering time to be less than directly rendering from all reference images. 1.

This paper presents a method for modeling the surface of an object from a sequence of range maps. Our method is based on a volumetric approach that produces a compact surface without boundary. It provides robustness through the use of interval analysis techniques and computational efficiency through hierarchical processing using octrees. 1.

This dissertation addresses the problem of scanning both the color and geometry of real objects and displaying realistic images of the scanned objects from arbitrary viewpoints. We present a complete system that uses a stereo camera system with active lighting to scan the object surface geometry and color as visible from one point of view. Scans expressed in sensor coordinates are registered into a single object-centered coordinate system by aligning both the color and geometry where the scans overlap. The range data are integrated into a surface model using a robust hierarchical space carving method. The fit of the resulting approximate mesh to data is improved and the mesh structure is simplified using mesh optimization methods. In addition, two methods are developed for view-dependent display of the reconstructed...

In this paper, we present a technique for rendering displacement mapped geometry using current graphics hardware. Our method renders a displacement by slicing through the enclosing volume. The #-test is used to render only the appropriate parts of every slice. The slices need not to be aligned with the base surface, e.g. it is possible to do screen-space aligned slicing. We then

The construction of a three-dimensional object model from a set of images taken from different viewpoints is an important problem in computer vision. One of the simplest ways to do this is to use the silhouettes of the object (the binary classification of images into object and background) to can construct a bounding volume for the object. To efficiently represent this volume, we use an octree, which represents the object as a tree of recursively subdivided cubes. We develop a new algorithm for computing the octree bounding volume from multiple silhouettes, and apply it to an object rotating on a turntable in front of a stationary camera. The algorithm performs a limited amount of processing for each viewpoint, and incrementally builds the volumetric model. The resulting algorithm requires less total computation than previous algorithms, runs in real-time, and builds a model whose resolution improves over time. Keywords: Computer vision, 3-D model construction, image sequence (motion) ...

this document. In addition we have outlined several of the tradeoffs in the design of an active optical triangulation based range sensor, discussed their fundamental limitations, and outlined the sources of noise both fundamental to the technology and to the Cyberware PS scanner which we use. Of all the errors introduced into range measurements mixed pixels are the worst. We have presented software solutions to remove mixed pixels along horizontal and vertical edges however a hardware solution [12] would be preferable. In addition, we have identified several other sources of noise and offered suggestions on how to remove them. For example, mixed-camera noise can be detected by examining the position and orientation of the scanner with respect to the geometry of the surface scanned and noting weather or not one of the virtual cameras is partially obscured. A similar solution would work to detect range bias. In addition, several reasons are given for painting the object including range artifacts from specular reflections, mixed pixels from intensity discontinuities, and range errors from concavities with reflective surfaces.

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INTRODUCTION In industrial manufacturing, product inspection is an important step in the production process. Since product reliability and quality management is of utmost importance in most mass-production facilities, 100 percent inspection of all parts, subassemblies, and finished products is often attempted. As a result, the inspection process is often the most costly stage in manufacturing. A central task for machine-based inspection is inspecting for visual appearance. Visual inspection seeks to identify both functional and cosmetic defects. At present, visual inspection in many manufacturing processes is carried out by human inspectors whose performance is generally inadequate and variable. The human visual system is adapted to perform in a world of variety and change; the visual inspection process, on the other hand, requires observing the same type of image repeatedly to detect anomalies. Moreover, the accuracy of human visual inspection declines with dull, endlessly rou