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Journal ArticleDOI

Piecewise planar scene reconstruction from sparse correspondences

01 Apr 2006-Image and Vision Computing (Butterworth-Heinemann)-Vol. 24, Iss: 4, pp 395-406
TL;DR: A novel method able to recover scene planes of arbitrary position and orientation from oriented images using homographies is presented and it is demonstrated that the reconstruction method can cope with large baseline changes.
About: This article is published in Image and Vision Computing.The article was published on 2006-04-01. It has received 61 citations till now. The article focuses on the topics: Orientation (computer vision) & Real image.
Citations
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Proceedings ArticleDOI
01 Sep 2009
TL;DR: A novel multi-view stereo method designed for image-based rendering that generates piecewise planar depth maps from an unordered collection of photographs is presented.
Abstract: We present a novel multi-view stereo method designed for image-based rendering that generates piecewise planar depth maps from an unordered collection of photographs.

273 citations


Cites background or methods from "Piecewise planar scene reconstructi..."

  • ...Various approaches for robustly detecting multiple planes in the scene [6, 10] and recoving piecewise planar reconstructions [1, 2, 11, 23, 27] have been proposed....

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  • ...Fitting multiple planes to sparse data has traditionally been done using robust regression on noisy 3D points [6, 11] although some techniques have used heuristics based on 3D lines [1]....

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Proceedings ArticleDOI
20 Jun 2011
TL;DR: This paper introduces a smoothly varying affine stitching field which is flexible enough to handle parallax while retaining the good extrapolation and occlusion handling properties of parametric transforms.
Abstract: Traditional image stitching using parametric transforms such as homography, only produces perceptually correct composites for planar scenes or parallax free camera motion between source frames. This limits mosaicing to source images taken from the same physical location. In this paper, we introduce a smoothly varying affine stitching field which is flexible enough to handle parallax while retaining the good extrapolation and occlusion handling properties of parametric transforms. Our algorithm which jointly estimates both the stitching field and correspondence, permits the stitching of general motion source images, provided the scenes do not contain abrupt protrusions.

242 citations


Cites methods from "Piecewise planar scene reconstructi..."

  • ...Finally, the field of image stitching is also related to various large displacement matching works such as those by Bhat et al. [3] and Fraundorfer et al. [ 10 ] and Brox et al. [25]....

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Patent
15 Jun 2010
TL;DR: In this article, a computer-readable media for reconstruction of a 3D scene from a collection of two-dimensional images is provided, where the computer vision algorithms may minimize an energy function that represents the relationships and similarities among features of the 2D images to assign pixels of the two dimensional images to planes in 3D scenes.
Abstract: Methods, systems, and computer-readable media for reconstruction a three-dimensional scene from a collection of two-dimensional images are provided. A computerized reconstruction system executes computer vision algorithms on the collection of two-dimensional images to identify candidate planes that are used to model visual characteristics of the environment depicted in the two-dimensional images. The computer vision algorithms may minimize an energy function that represents the relationships and similarities among features of the two-dimensional images to assign pixels of the two dimensional images to planes in the three dimensional scene. The three-dimensional scene is navigable and depicts viewpoint transitions between multiple two-dimensional images.

108 citations

Proceedings ArticleDOI
23 Jun 2014
TL;DR: This work presents a novel approach for producing dense reconstructions from multiple images and from the underlying sparse Structure-from-Motion (SfM) data in an efficient way and assumes piecewise planarity of man-made scenes and exploits both sparse visibility and a fast over-segmentation of the images.
Abstract: State-of-the-art Multi-View Stereo (MVS) algorithms deliver dense depth maps or complex meshes with very high detail, and redundancy over regular surfaces. In turn, our interest lies in an approximate, but light-weight method that is better to consider for large-scale applications, such as urban scene reconstruction from ground-based images. We present a novel approach for producing dense reconstructions from multiple images and from the underlying sparse Structure-from-Motion (SfM) data in an efficient way. To overcome the problem of SfM sparsity and textureless areas, we assume piecewise planarity of man-made scenes and exploit both sparse visibility and a fast over-segmentation of the images. Reconstruction is formulated as an energy-driven, multi-view plane assignment problem, which we solve jointly over superpixels from all views while avoiding expensive photoconsistency computations. The resulting planar primitives--defined by detailed superpixel boundaries--are computed in about 10 seconds per image.

71 citations


Cites background from "Piecewise planar scene reconstructi..."

  • ...This approach can capture multiple planes, while not suffering from the difficulties of direct fitting of global planes [29], or of local plane growing either in the image [10] or in the sparse point cloud [5]....

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  • ...[10, 11], produces denser results than PMVS [11], and is much faster than, e....

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  • ...[10] iterates between photoconsistent support region growing and updating the plane parameters....

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Proceedings ArticleDOI
07 Jun 2015
TL;DR: This work proposes a novel surface reconstruction method based on image edges, superpixels and second-order smoothness constraints, producing meshes comparable to classic MVS surfaces in quality but orders of magnitudes faster.
Abstract: Multi-View-Stereo (MVS) methods aim for the highest detail possible, however, such detail is often not required. In this work, we propose a novel surface reconstruction method based on image edges, superpixels and second-order smoothness constraints, producing meshes comparable to classic MVS surfaces in quality but orders of magnitudes faster. Our method performs per-view dense depth optimization directly over sparse 3D Ground Control Points (GCPs), hence, removing the need for view pairing, image rectification, and stereo depth estimation, and allowing for full per-image parallelization. We use Structure-from-Motion (SfM) points as GCPs, but the method is not specific to these, e.g. LiDAR or RGB-D can also be used. The resulting meshes are compact and inherently edge-aligned with image gradients, enabling good-quality lightweight per-face flat renderings. Our experiments demonstrate on a variety of 3D datasets the superiority in speed and competitive surface quality.

65 citations


Cites background from "Piecewise planar scene reconstructi..."

  • ...Most of these assume piecewise planarity and do not handle non-planar regions [64, 54, 15, 53, 4]....

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References
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Journal ArticleDOI
TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Abstract: A new paradigm, Random Sample Consensus (RANSAC), for fitting a model to experimental data is introduced. RANSAC is capable of interpreting/smoothing data containing a significant percentage of gross errors, and is thus ideally suited for applications in automated image analysis where interpretation is based on the data provided by error-prone feature detectors. A major portion of this paper describes the application of RANSAC to the Location Determination Problem (LDP): Given an image depicting a set of landmarks with known locations, determine that point in space from which the image was obtained. In response to a RANSAC requirement, new results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form. These results provide the basis for an automatic system that can solve the LDP under difficult viewing

23,396 citations

Book
01 Jan 2000
TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
Abstract: From the Publisher: A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. The book covers the geometric principles and how to represent objects algebraically so they can be computed and applied. The authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly.

15,558 citations

01 Jan 2001
TL;DR: This book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts and it will show the best book collections and completed collections.
Abstract: Downloading the book in this website lists can give you more advantages. It will show you the best book collections and completed collections. So many books can be found in this website. So, this is not only this multiple view geometry in computer vision. However, this book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts. This is simple, read the soft file of the book and you get it.

14,282 citations


"Piecewise planar scene reconstructi..." refers background in this paper

  • ...Keywords: Planar homography; 3D Scene reconstruction; Affine invariant regions...

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Journal ArticleDOI
TL;DR: The high utility of MSERs, multiple measurement regions and the robust metric is demonstrated in wide-baseline experiments on image pairs from both indoor and outdoor scenes.

3,422 citations

Proceedings ArticleDOI
01 Jan 2002
TL;DR: The wide-baseline stereo problem, i.e. the problem of establishing correspondences between a pair of images taken from different viewpoints, is studied and an efficient and practically fast detection algorithm is presented for an affinely-invariant stable subset of extremal regions, the maximally stable extremal region (MSER).
Abstract: The wide-baseline stereo problem, i.e. the problem of establishing correspondences between a pair of images taken from different viewpoints is studied. A new set of image elements that are put into correspondence, the so called extremal regions , is introduced. Extremal regions possess highly desirable properties: the set is closed under (1) continuous (and thus projective) transformation of image coordinates and (2) monotonic transformation of image intensities. An efficient (near linear complexity) and practically fast detection algorithm (near frame rate) is presented for an affinely invariant stable subset of extremal regions, the maximally stable extremal regions (MSER). A new robust similarity measure for establishing tentative correspondences is proposed. The robustness ensures that invariants from multiple measurement regions (regions obtained by invariant constructions from extremal regions), some that are significantly larger (and hence discriminative) than the MSERs, may be used to establish tentative correspondences. The high utility of MSERs, multiple measurement regions and the robust metric is demonstrated in wide-baseline experiments on image pairs from both indoor and outdoor scenes. Significant change of scale (3.5×), illumination conditions, out-of-plane rotation, occlusion, locally anisotropic scale change and 3D translation of the viewpoint are all present in the test problems. Good estimates of epipolar geometry (average distance from corresponding points to the epipolar line below 0.09 of the inter-pixel distance) are obtained.

3,400 citations