We describe and demonstrate an algorithm that takes as input an unorganized set of points fx1�:::�xng IR 3 on or near an unknown manifold M, and produces as output a simplicial surface that approximates M. Neither the topology, the presence of boundaries, nor the geometry of M are assumed to be known in advance — all are inferred automatically from the data. This problem naturally arises in a variety of practical situations such as range scanning an object from multiple view points, recovery of biological shapes from two-dimensional slices, and interactive surface sketching.

Image-space simplifications have been used to accelerate the calculation of computer graphic images since the dawn of visual simulation. Texture mapping has been used to provide a means by which images may themselves be used as display primitives. The work reported by this paper endeavors to carry this concept to its logical extreme by using interpolated images to portray three-dimensional scenes. The special-effects technique of morphing, which combines interpolation of texture maps and their shape, is applied to computing arbitrary intermediate frames from an array of prestored images. If the images are a structured set of views of a 3D object or scene, intermediate frames derived by morphing can be used to approximate intermediate 3D transformations of the object or scene. Using the view interpolation approach to synthesize 3D scenes has two main advantages. First, the 3D representation of the scene may be replaced with images. Second, the image synthesis time is independent of the scene complexity. The correspondence between images, required for the morphing method, can be predetermined automatically using the range data associated with the images. The method is further accelerated by a quadtree decomposition and a view-independent visible priority. Our experiments have shown that the morphing can be performed at interactive rates on today’s high-end personal computers. Potential applications of the method include virtual holograms, a walkthrough in a virtual environment, image-based primitives and incremental rendering. The method also can be used to greatly accelerate the computation of motion blur and soft shadows cast by area light sources.

A methodology for evaluating range image segmentation algorithms is proposed. This methodology involves (a) a common set of 40 laser range finder images and 40 structured light scanner images that have manually specified ground truth and (b) a set of defined performance metrics for instances of correctly segmented, missed and noise regions, over- and under-segmentation, and accuracy of the recovered geometry. A tool is used to objectively compare a machine generated segmentation against the specified ground truth. Four research groups have contributed to evaluate their own algorithm for segmenting a range image into planar patches.

Leonard McMillan Jr. An Image-Based Approach to Three-Dimensional Computer Graphics (Under the direction of Gary Bishop) The conventional approach to three-dimensional computer graphics produces images from geometric scene descriptions by simulating the interaction of light with matter. My research explores an alternative approach that replaces the geometric scene description with perspective images and replaces the simulation process with data interpolation. I derive an image-warping equation that maps the visible points in a reference image to their correct positions in any desired view. This mapping from reference image to desired image is determined by the center-of-projection and pinhole-camera model of the two images and by a generalized disparity value associated with each point in the reference image. This generalized disparity value, which represents the structure of the scene, can be determined from point correspondences between multiple reference images. The image-warpi...

IEEE Computer Society Abstract—Depth from triangulation has traditionally been investigated in a number of independent threads of research, with methods such as stereo, laser scanning, and coded structured light considered separately. In this paper, we propose a common framework called spacetime stereo that unifies and generalizes many of these previous methods. To show the practical utility of the framework, we develop two new algorithms for depth estimation: depth from unstructured illumination change and depth estimation in dynamic scenes. Based on our analysis, we show that methods derived from the spacetime stereo framework can be used to recover depth in situations in which existing methods perform poorly. Index Terms—Depth from triangulation, stereo, spacetime stereo. 1

Structures of dynamic scenes can only be recovered using a real-time range sensor. Focus analysis offers a direct solution to fast and dense range estimation. It is computational efficient as it circumvents the correspondence problem faced by stereo and feature tracking in structure from motion. However, accurate depth estimation requires theoretical and practical solutions to a variety of problems including recovery of textureless surfaces, precise blur estimation, and magnification variations caused by defocusing. Both textured and textureless surfaces are recovered using an illumination pattern that is projected via the same optical path used to acquire images. The illumination pattern is optimized to ensure maximum accuracy and spatial resolution in computed depth. A prototype focus range sensor has been developed that produces up to 512x480 depth estimates at 30 Hz with an accuracy better than 0.3%. In addition, a microscopic shape from focus sensor is described that uses the deri...

We present a survey of the most significant techniques, used in the last few years, concerning the coded structured light methods employed to get 3D information. In fact, depth perception is one of the most important subjects in computer vision. Stereovision is an attractive and widely used method, but, it is rather limited to make 3D surface maps, due to the correspondence problem. The correspondence problem can be improved using a method based on structured light concept, projecting a given pattern on the measuring surfaces. However, some relations between the projected pattern and the reflected one must be solved. This relationship can be directly found codifying the projected light, so that, each imaged region of the projected pattern carries the needed information to solve the correspondence problem.

not use color information in order to focus on geometric aspects. Note how our method eliminates noise from the range image while introducing real detail. The surface normals are of the same quality or better than those from photometric stereo, while most of the low-frequency bias has been eliminated. Range scanning, manual 3D editing, and other modeling approaches can provide information about the geometry of surfaces in the form of either 3D positions (e.g., triangle meshes or range images) or orientations (normal maps or bump maps). We present an algorithm that combines these two kinds of estimates to produce a new surface that approximates both. Our formulation is linear, allowing it to operate efficiently on complex meshes commonly used in graphics. It also treats high- and low-frequency components separately, allowing it to optimally combine outputs from data sources such as stereo triangulation and photometric stereo, which have different error-vs.-frequency characteristics. We demonstrate the ability of our technique to both recover high-frequency details and avoid low-frequency bias, producing surfaces that are more widely applicable than position or orientation data alone. 1

Environment matting is a generalization of traditional bluescreen matting. By photographing an object in front of a sequence of structured light backdrops, a set of approximate light-transport paths through the object can be computed. The original environment matting research chose a middle ground---using a moderate number of photographs to produce results that were reasonably accurate for many objects. In this work, we extend the technique in two opposite directions: recovering a more accurate model at the expense of using additional structured light backdrops, and obtaining a simplified matte using just a single backdrop. The first extension allows for the capture of complex and subtle interactions of light with objects, while the second allows for video capture of colorless objects in motion. CR Categories: I.2.10 [Artificial Intelligence]: Vision and Scene Understanding --- modeling and recovery of physical attributes; I.3.3 [Computer Graphics]: Picture /Image Generation --- displ...

This paper attempts to present a comprehensive summary of research results in the use of visual information to control robot manipulators and related mechanisms. An extensive bibliography is provided which also includes important papers from the elemental disciplines upon which visual servoing is based. The research results are discussed in terms of historical context, commonality of function, algorithmic approach and method of implementation. 1 Introduction This paper presents the history, and reviews current research into the use of visual information for the control of robot manipulators and mechanisms. Visual control of manipulators promises substantial advantages when working with targets whose position is unknown, or with manipulators which may be flexible or inaccurate. The reported use of visual information to guide robots, or more generally mechanisms, is quite extensive and encompasses manufacturing applications, teleoperation, missile tracking cameras, fruit picking as well...