Polygon optimisation for the modelling of planar range data

Authors:
Samuel Nunes;Daniel Almeida;Eddy Loke;Hans du Buf
Affiliations:
Vision Laboratory, University of Algarve, Faro, Portugal;Vision Laboratory, University of Algarve, Faro, Portugal;Vision Laboratory, University of Algarve, Faro, Portugal;Vision Laboratory, University of Algarve, Faro, Portugal
Venue:
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
Year:
2005

Citing 3
Cited 0

An Experimental Comparison of Range Image Segmentation Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Geometry in C

Computational Geometry in C
Range image segmentation using local approximation of scan lines with application to CAD model acquisition

Machine Vision and Applications

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Abstract

In this paper we present efficient and fast algorithms for the reconstruction of scenes or objects using range image data. Assuming that a good segmentation is available, we concentrate on the polygonisation, triangulation and optimisation, i.e. both triangle reduction and adaptive edge filtering to improve edge linearity. In the processing, special attention is given to complex edge junctions. In a last step, vertex neighbourhoods are analysed in order to robustly attribute depth to the triangle list from the noisy range data.