Geometric data abstraction using B-splines for range image segmentation

Mörwald, Thomas; Richtsfeld, Andreas; Prankl, Johann; Zillich, Michael; Vincze, Markus

doi:10.1109/icra.2013.6630569

Cited by 19 publications

(13 citation statements)

References 20 publications

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“…DARP support for non-planar non-smooth objects should also be improved, perhaps by obtaining a parameterization of the 3D surface that would allow flattening the non-planar object for obtaining a planar representation of it. This would use an approach similar to the one described in [43], where B-splines surfaces are fitted to point clouds obtained from RGB-D sensors. With respect to DARC, GPU optimization should also be considered.…”

Section: Discussionmentioning

confidence: 99%

Depth-assisted rectification for real-time object detection and pose estimation

Lima

Simões

Uchiyama

et al. 2015

Machine Vision and Applications

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RGB-D sensors have become in recent years a product of easy access to general users. They provide both a color image and a depth image of the scene and, besides being used for object modeling, they can also offer important cues for object detection and tracking in real-time. In this context, the work presented in this paper investigates the use of consumer RGB-D sensors for object detection and pose estimation from natural features. Two methods based on depth-assisted rectification are proposed, which transform features extracted from the color image to a canonical view using depth data in order to obtain a representation invariant to rotation, scale and perspective distortions. While one method is suitable for textured objects, either planar or non-planar, the other method focuses on texture-less planar objects. Qualitative and quantitative evaluations of the proposed methods are performed, showing that they can obtain better results than some existing methods for object detection and pose estimation, especially when dealing with oblique poses.

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Section: Discussionmentioning

confidence: 99%

Depth-assisted rectification for real-time object detection and pose estimation

Lima

Simões

Uchiyama

et al. 2015

Machine Vision and Applications

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“…Mo¨rwald et al [5] showed an approach to reconstruct curved geometries with NURBS. First the point cloud is over-segmented into planar patches.…”

Section: Previous Workmentioning

confidence: 99%

“…Region-based segmentations like [4], [5] use normals at each point as region growing criterion for locally planar patches. As Holz et al [6] state normal estimation on a complete point cloud can be quite expensive.…”

Section: Previous Workmentioning

confidence: 99%

Quadtree-based polynomial polygon fitting

Hampp

Bormann

2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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In this paper, we present a novel method for surface reconstruction with a low execution time for segmenting and representing scattered scenes accurately. The surfaces are described in a memory-efficient fashion as polynomial functions and polygons. Segmentation and parameter determination is done in one pass by using a quadtree on ordered point clouds, which results in a complexity of O(log n).This paper includes an evaluation with respect to reconstruction accuracy, segmentation precision, execution time and compression ratio of everyday indoor scenes. Our surface reconstruction algorithm outperforms comparable approaches with respect to execution time and accuracy. More importantly, the new technique handles curved shapes accurately and enables complex tasks like 3D mapping for mobile robots in an unknown environment.

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“…A considerable reduction in computational complexity has been depicted by the experimental results. Andreas Richtsfeld et al 2013 [11] The following paper provide a new strategy to RGB-D sensing unit data described by B-spline surfaces and related boundaries to parametric surface models. Further, it has depicted that how precisely curve fitting calculates smooth boundaries as well as enhances the provided sensor data whenever using colour.…”

Section: Related Workmentioning

confidence: 99%

A Review on the Artificial Bee Colony & Clahe Based Hybrid Hough Transform For Efficient Lane Detection

Multani

Marwaha²

2017

IJECS

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This paper represents that lane coloration has become popular in real time vehicular ad-hoc system. Lane detection is normally helpful to localize path limits, determine undesired lane variations, and to enable approximation of the upcoming geometry of the road. There are different types of methods that are used for detecting lines, curves and ellipses i.e. hough transform, clustering and curve fitting. The overall objective of this paper is to providing better performance in lane coloration algorithm. The methods developed till now are working effectively as well as giving good results.

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Geometric data abstraction using B-splines for range image segmentation

Cited by 19 publications

References 20 publications

Depth-assisted rectification for real-time object detection and pose estimation

Depth-assisted rectification for real-time object detection and pose estimation

Quadtree-based polynomial polygon fitting

A Review on the Artificial Bee Colony & Clahe Based Hybrid Hough Transform For Efficient Lane Detection

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