An estimation-based approach for range image segmentation: on the reliability of primitive extraction

Wang, Guoyu; Houkes, Z.; Ji, Guangrong; Zheng, Bing; Li, Xin

doi:10.1016/s0031-3203(02)00050-x

Cited by 17 publications

(10 citation statements)

References 20 publications

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“…A distinction is made between segmentation based on normal vectors, 39,40 curvatures, [41][42][43][44][45] and fitting polynomials. [46][47][48] Existing techniques using low-degree polynomial fitting for surface segmentation consider planar patches 48 and quadratic patches, [49][50][51] such as circular cylinders 52 and ellipsoidal surfaces. 53 These techniques are often not suited to segment intensity images.…”

Section: Related Workmentioning

confidence: 99%

Image segmentation with adaptive region growing based on a polynomial surface model

Deboeverie

Veelaert

Philips

2013

J. Electron. Imaging

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Abstract.A new method for segmenting intensity images into smooth surface segments is presented. The main idea is to divide the image into flat, planar, convex, concave, and saddle patches that coincide as well as possible with meaningful object features in the image. Therefore, we propose an adaptive region growing algorithm based on low-degree polynomial fitting. The algorithm uses a new adaptive thresholding technique with the L ∞ fitting cost as a segmentation criterion. The polynomial degree and the fitting error are automatically adapted during the region growing process. The main contribution is that the algorithm detects outliers and edges, distinguishes between strong and smooth intensity transitions and finds surface segments that are bent in a certain way. As a result, the surface segments corresponding to meaningful object features and the contours separating the surface segments coincide with real-image object edges. Moreover, the curvature-based surface shape information facilitates many tasks in image analysis, such as object recognition performed on the polynomial representation. The polynomial representation provides good image approximation while preserving all the necessary details of the objects in the reconstructed images. The method outperforms existing techniques when segmenting images of objects with diffuse reflecting surfaces.

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Section: Related Workmentioning

confidence: 99%

Image segmentation with adaptive region growing based on a polynomial surface model

Deboeverie

Veelaert

Philips

2013

J. Electron. Imaging

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“…In [5], Dai et al describe recovery of paraboloid geometric parameters 1 by linear least squares, without considering uncertainty. In [17] Wang et al studied quadric extraction in the context of range image segmentation, including quantified uncertainty in the algebraic (not geometric) patch parameters, but not on the input points. Our fitting algorithm quantifies both input and output uncertainty and recovers geometric parameters of bounded patches.…”

Section: A Related Workmentioning

confidence: 99%

“…The latter holds for circular boundaries, which we use for circular paraboloids. Let κ be the surface curvature and d c the bounding circle radius; circular paraboloids are then defined by (12)(13)(14)(15)(16)(17) …”

Section: A Paraboloidsmentioning

confidence: 99%

Curved surface contact patches with quantified uncertainty

Vona

Kanoulas

2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-We introduce a set of 10 bounded curved-surface patch types suitable for modeling local contact regions both in the environment and on a robot. We present minimal geometric parameterizations using the exponential map for spatial pose both in the usual 6DoF case and also for patches with revolute symmetry that have only 5DoF. We then give an algorithm to fit any patch type to point samples of a surface, with quantified uncertainty both in the input points (including nonuniform variance, common in data from range sensors) and in the output patch. Finally, we outline how such patches can be composed into a spatial patch map of the available contact surfaces both on and around a robot.

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“…The bottom-up approach expands the cluster starting from an initial seed point by measuring the similarity criteria [8,9] of unallocated neighboring points. Chang and Park [8] combined the Bayesian theory and Markov random field (MRF) approach to access the prior regional shape, which extracts parametric surfaces by representing the scanned objects by a series of local planar surfaces.…”

Section: B Region-based Segmentationmentioning

confidence: 99%

“…Chang and Park [8] combined the Bayesian theory and Markov random field (MRF) approach to access the prior regional shape, which extracts parametric surfaces by representing the scanned objects by a series of local planar surfaces. Wang et al [9] developed a reliable region-growing and merging algorithm based on the uncertainty of the segmented data and demonstrated on simple geometries.…”

Section: B Region-based Segmentationmentioning

confidence: 99%

Rapid clustering of colorized 3D point cloud data for reconstructing building interiors

Sareen

Knopf

Canas

2010

2010 International Symposium on Optomechatronic Technologies

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ISOT 2010 International Symposium on Optomechatronic Technologies, Toronto, ON, October 25-27, 2010, pp. 1-6 The material in this document is covered by the provisions of the Copyright Act, by Canadian laws, policies, regulations and international agreements. Such provisions serve to identify the information source and, in specific instances, to prohibit reproduction of materials without written permission. For more information visit http://laws.justice.gc.ca/en/showtdm/cs/C-42Les renseignements dans ce document sont protégés par la Loi sur le droit d'auteur, par les lois, les politiques et les règlements du Canada et des accords internationaux. Ces dispositions permettent d'identifier la source de l'information et, dans certains cas, d'interdire la copie de documents sans permission écrite. Pour obtenir de plus amples renseignements : http://lois.justice.gc.ca/fr/showtdm/cs/C-42

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An estimation-based approach for range image segmentation: on the reliability of primitive extraction

Cited by 17 publications

References 20 publications

Image segmentation with adaptive region growing based on a polynomial surface model

Image segmentation with adaptive region growing based on a polynomial surface model

Curved surface contact patches with quantified uncertainty

Rapid clustering of colorized 3D point cloud data for reconstructing building interiors

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