Book•
The Geometry of Multiple Images: The Laws That Govern the Formation of Multiple Images of a Scene and Some of Their Applications
05 Mar 2001-
TL;DR: The state of knowledge in one subarea of vision is described, the geometric laws that relate different views of a scene from the perspective of various types of geometries, which is a unified framework for thinking about many geometric problems relevant to vision.
Abstract: From the Publisher:
with contributions from Theo Papadopoulo
Over the last forty years, researchers have made great strides in elucidating the laws of image formation, processing, and understanding by animals, humans, and machines. This book describes the state of knowledge in one subarea of vision, the geometric laws that relate different views of a scene. Geometry, one of the oldest branches of mathematics, is the natural language for describing three-dimensional shapes and spatial relations. Projective geometry, the geometry that best models image formation, provides a unified framework for thinking about many geometric problems relevant to vision. The book formalizes and analyzes the relations between multiple views of a scene from the perspective of various types of geometries. A key feature is that it considers Euclidean and affine geometries as special cases of projective geometry.
Images play a prominent role in computer communications. Producers and users of images, in particular three-dimensional images, require a framework for stating and solving problems. The book offers a number of conceptual tools and theoretical results useful for the design of machine vision algorithms. It also illustrates these tools and results with many examples of real applications.
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TL;DR: This paper has designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms.
Abstract: 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.
7,458 citations
TL;DR: Details of a system that allows for an evolutionary introduction of depth perception into the existing 2D digital TV framework are presented and a comparison with the classical approach of "stereoscopic" video is compared.
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1,560 citations
TL;DR: This work reviews recent advances in computational stereo, focusing primarily on three important topics: correspondence methods, methods for occlusion, and real-time implementations.
Abstract: Extraction of three-dimensional structure of a scene from stereo images is a problem that has been studied by the computer vision community for decades. Early work focused on the fundamentals of image correspondence and stereo geometry. Stereo research has matured significantly throughout the years and many advances in computational stereo continue to be made, allowing stereo to be applied to new and more demanding problems. We review recent advances in computational stereo, focusing primarily on three important topics: correspondence methods, methods for occlusion, and real-time implementations. Throughout, we present tables that summarize and draw distinctions among key ideas and approaches. Where available, we provide comparative analyses and we make suggestions for analyses yet to be done.
1,274 citations
TL;DR: A complete system to build visual models from camera images is presented and a combined approach with view-dependent geometry and texture is presented, as an application fusion of real and virtual scenes is also shown.
Abstract: In this paper a complete system to build visual models from camera images is presented. The system can deal with uncalibrated image sequences acquired with a hand-held camera. Based on tracked or matched features the relations between multiple views are computed. From this both the structure of the scene and the motion of the camera are retrieved. The ambiguity on the reconstruction is restricted from projective to metric through self-calibration. A flexible multi-view stereo matching scheme is used to obtain a dense estimation of the surface geometry. From the computed data different types of visual models are constructed. Besides the traditional geometry- and image-based approaches, a combined approach with view-dependent geometry and texture is presented. As an application fusion of real and virtual scenes is also shown.
1,029 citations
Cites background from "The Geometry of Multiple Images: Th..."
...A more in depth description can be found in Faugeras et al. (2001) and Hartley and Zisserman (2000)....
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TL;DR: A perceptual grouping process that permits the robust identification and localization of environmental features from the sparse and noisy sonar data, and a map joining technique that allows the system to build a sequence of independent limited-size stochastic maps and join them in a globally consistent way.
Abstract: In this paper we describe a new technique for the creation of featurebased stochastic maps using standard Polaroid sonar sensors. The fundamental contributions of our proposal are: (1) a perceptual grouping process that permits the robust identification and localization of environmental features, such as straight segments and corners, from the sparse and noisy sonar data; (2) a map joining technique that allows the system to build a sequence of independent limited-size stochastic maps and join them in a globally consistent way; (3) a robust mechanism to determine which features in a stochastic map correspond to the same environment feature, allowing the system to update the stochastic map accordingly, and perform tasks such as revisiting and loop closing. We demonstrate the practicality of this approach by building a geometric map of a medium size, real indoor environment, with several people moving around the robot. Maps built from laser data for the same experiment are provided for comparison.
577 citations
Cites background from "The Geometry of Multiple Images: Th..."
...However, a great deal of research in the last decade has shown that, using a single moving camera, it is possible to determine both the camera motion and the environment structure (Hartley and Zisserman 2000; Faugeras and Luong 2001)....
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