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The Geometry of Multiple Images: The Laws That Govern the Formation of Multiple Images of a Scene and Some of Their Applications
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TLDR
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.read more
Citations
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Journal ArticleDOI
3D reconstruction for a scanning electron microscope
TL;DR: In this paper, an algorithm for the reconstruction of the 3D shape of the surface of a micro-object from a stereo pair of images obtained on a raster electron microscope (REM) has been considered.
Book ChapterDOI
Robust linear auto-calibration of a moving camera from image sequences
TL;DR: A robust linear method for auto-calibration of a moving camera from image sequences that uses known linear equations that are weighted by variable factors and achieves a higher estimation accuracy.
Journal ArticleDOI
PhotoSketch: a photocentric urban 3D modeling system
George Wolberg,Siavash Zokai +1 more
TL;DR: The contribution of this work is that it merges the benefits of multiview geometry, an intuitive sketching interface, and dynamic texture mapping to produce lightweight photorealistic 3D models of buildings.
Journal ArticleDOI
Outlier correction from uncalibrated image sequence using the Triangulation method
Jae-Hak Kim,Joon Hee Han +1 more
TL;DR: This work proposes a robust algorithm for estimating the projective reconstruction from image features using the RANSAC-based Triangulation method, and shows that errors can be reduced significantly compared to the previous research as a result of robustly estimatedprojective reconstruction.
Book ChapterDOI
Is Dense Optic Flow Useful to Compute the Fundamental Matrix
TL;DR: This paper considers the state-of-the-art optic flow method of Brox et al. (ECCV 2004) and compares the results computed from its dense flow fields to the ones estimated from a RANSAC method that is based on a sparse set of SIFT-matches.