Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web.

/pdf/a-taxonomy-and-evaluation-of-dense-two-frame-stereo-4c20etkubp.pdf

A taxonomy and evaluation of dense two-frame stereo correspondence algorithms

A number of techniques have been proposed for flying through scenes by redisplaying previously rendered or digitized views. Techniques have also been proposed for interpolating between views by warping input images, using depth information or correspondences between multiple images. In this paper, we describe a simple and robust method for generating new views from arbitrary camera positions without depth information or feature matching, simply by combining and resampling the available images. The key to this technique lies in interpreting the input images as 2D slices of a 4D function the light field. This function completely characterizes the flow of light through unobstructed space in a static scene with fixed illumination. We describe a sampled representation for light fields that allows for both efficient creation and display of inward and outward looking views. We hav e created light fields from large arrays of both rendered and digitized images. The latter are acquired using a video camera mounted on a computer-controlled gantry. Once a light field has been created, new views may be constructed in real time by extracting slices in appropriate directions. Since the success of the method depends on having a high sample rate, we describe a compression system that is able to compress the light fields we have generated by more than a factor of 100:1 with very little loss of fidelity. We also address the issues of antialiasing during creation, and resampling during slice extraction. CR Categories: I.3.2 [Computer Graphics]: Picture/Image Generation — Digitizing and scanning, Viewing algorithms; I.4.2 [Computer Graphics]: Compression — Approximate methods Additional keywords: image-based rendering, light field, holographic stereogram, vector quantization, epipolar analysis

/pdf/light-field-rendering-3fds6lbjg4.pdf

Light field rendering

This paper discusses a new method for capturing the complete appearance of both synthetic and real world objects and scenes, representing this information, and then using this representation to render images of the object from new camera positions. Unlike the shape capture process traditionally used in computer vision and the rendering process traditionally used in computer graphics, our approach does not rely on geometric representations. Instead we sample and reconstruct a 4D function, which we call a Lumigraph. The Lumigraph is a subset of the complete plenoptic function that describes the flow of light at all positions in all directions. With the Lumigraph, new images of the object can be generated very quickly, independent of the geometric or illumination complexity of the scene or object. The paper discusses a complete working system including the capture of samples, the construction of the Lumigraph, and the subsequent rendering of images from this new representation.

The lumigraph

Inferring scene geometry and camera motion from a stream of images is possible in principle, but is an ill-conditioned problem when the objects are distant with respect to their size. We have developed a factorization method that can overcome this difficulty by recovering shape and motion under orthography without computing depth as an intermediate step. An image stream can be represented by the 2FxP measurement matrix of the image coordinates of P points tracked through F frames. We show that under orthographic projection this matrix is of rank 3. Based on this observation, the factorization method uses the singular-value decomposition technique to factor the measurement matrix into two matrices which represent object shape and camera rotation respectively. Two of the three translation components are computed in a preprocessing stage. The method can also handle and obtain a full solution from a partially filled-in measurement matrix that may result from occlusions or tracking failures. The method gives accurate results, and does not introduce smoothing in either shape or motion. We demonstrate this with a series of experiments on laboratory and outdoor image streams, with and without occlusions.

/pdf/shape-and-motion-from-image-streams-under-orthography-a-3mcosr5hgx.pdf

Shape and motion from image streams under orthography: a factorization method

Image-based rendering is a powerful new approach for generating real-time photorealistic computer graphics. It can provide convincing animations without an explicit geometric representation. We use the “plenoptic function” of Adelson and Bergen to provide a concise problem statement for image-based rendering paradigms, such as morphing and view interpolation. The plenoptic function is a parameterized function for describing everything that is visible from a given point in space. We present an image-based rendering system based on sampling, reconstructing, and resampling the plenoptic function. In addition, we introduce a novel visible surface algorithm and a geometric invariant for cylindrical projections that is equivalent to the epipolar constraint defined for planar projections.

/pdf/plenoptic-modeling-an-image-based-rendering-system-3tsz987p50.pdf

Plenoptic modeling: an image-based rendering system

We present a technique for building a three-dimensional description of a static scene from a dense sequence of images. These images are taken in such rapid succession that they form a solid block of data in which the temporal continuity from image to image is approximately equal to the spatial continuity in an individual image. The technique utilizes knowledge of the camera motion to form and analyze slices of this solid. These slices directly encode not only the three-dimensional positions of objects, but also such spatiotemporal events as the occlusion of one object by another. For straight-line camera motions, these slices have a simple linear structure that makes them easier to analyze. The analysis computes the three-dimensional positions of object features, marks occlusion boundaries on the objects, and builds a three-dimensional map of “free space.” In our article, we first describe the application of this technique to a simple camera motion, and then show how projective duality is used to extend the analysis to a wider class of camera motions and object types that include curved and moving objects.

/pdf/epipolar-plane-image-analysis-an-approach-to-determining-55gt8zm0ip.pdf

David H. Marimont

Papers

Epipolar-plane image analysis: An approach to determining structure from motion

Determining scene structure from a moving camera: Epipolar-plane image analysis