By Theo Moons, Luc van Gool, Maarten Vergauwen

ISBN-10: 1601982844

ISBN-13: 9781601982841

3D Reconstruction from a number of pictures, half 1: rules discusses and explains the right way to extract three-d (3D) versions from simple photos. specifically, the 3D info is got from pictures for which the digital camera parameters are unknown. the foundations underlying such uncalibrated structure-from-motion equipment are defined. First, a brief assessment of 3D acquisition applied sciences places such tools in a much wider context and highlights their vital merits. Then, the particular thought in the back of this line of study is given. The authors have attempted to maintain the textual content maximally self-contained, for this reason additionally fending off counting on an in depth wisdom of the projective ideas that sometimes look in texts approximately self-calibration 3D equipment. relatively, mathematical factors which are extra amenable to instinct are given. the reason of the idea comprises the stratification of reconstructions acquired from snapshot pairs in addition to metric reconstruction at the foundation of greater than photographs mixed with a few extra wisdom concerning the cameras used. 3D Reconstruction from a number of photographs, half 1: ideas is the 1st of a three-part Foundations and tendencies educational in this subject written by means of an identical authors. half II will specialise in simpler information regarding tips on how to enforce such uncalibrated structure-from-motion pipelines, whereas half III will define an instance pipeline with additional implementation concerns particular to this actual case, and together with a consumer consultant.

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Extra resources for 3D Reconstruction from Multiple Images, Part 1: Principles

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This, however, does not mean that this model is perfect. In reality the center of radial distortion (now assumed to be the principal point) sometimes changes when the focal length is altered. This effect cannot be modeled with this approach. In the remainder of the text we will assume that radial distortion has been removed from all images if present, unless stated otherwise. 6 Explicit Camera Calibration As explained before a perspective camera can be described by its internal and external parameters.

And, when ρ1 is found, the Euclidean transformation M of the scene point M is found as well. 21). 21) is therefore referred to as a system of Euclidean reconstruction equations for the scene and the 3D points M satisfying these equations constitute a Euclidean reconstruction of 342 Principles of Passive 3D Reconstruction the scene. As a matter of fact, better than Euclidean reconstruction is often not needed, as the 3D shape of the objects in the scene is perfectly retrieved, only not their position relative to the world coordinate frame, which is completely irrelevant in many applications.

The coordinates ¯ provide a 3D reconstruction of the scene point M up to an unknown M 3D similarity, as expected. We could have seen this additional scaling issue coming also intuitively. If one were to scale a scene together with the cameras in it, then this would have no impact on the images. In terms of the relative camera positions, this would only change the distance between them, not their relative orientations or the relative direction in which one camera is displaced with respect to the other.

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3D Reconstruction from Multiple Images, Part 1: Principles by Theo Moons, Luc van Gool, Maarten Vergauwen


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