isprsarchives XXXVIII 5 W12 97 2011
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![Figure 1: Three examples of ellipsoids computed over three ar-eas of interest of distinct dimensionalities for the TLS dataset (atripod over a low and sparse vegetation – height colored).](https://thumb-ap.123doks.com/thumbv2/123dok/3226749.1395844/3.595.108.243.111.257/figure-examples-ellipsoids-computed-distinct-dimensionalities-vegetation-colored.webp)
![Figure 4: Optimal neighborhood radius retrieval (TLSthe neighborhood radius over 50 points within the white (c) andVariation of the shape features and3D point cloud colored with dataset)](https://thumb-ap.123doks.com/thumbv2/123dok/3226749.1395844/4.595.61.287.189.387/figure-optimal-neighborhood-retrieval-neighborhood-andvariation-features-dataset.webp)
![Figure 5: Radius selection (r) and dimensionality labelling for (a) ALSG, (b) ALSF , (c) MMSU, and (d) MMSF datasets.](https://thumb-ap.123doks.com/thumbv2/123dok/3226749.1395844/5.595.59.287.372.519/figure-radius-selection-dimensionality-labelling-alsg-alsf-datasets.webp)
![Figure 8: Dimensionality labelling for the MMSF dataset using aconstant neighborhood size for the whole point cloud (left), andthe optimal value per point selected with Ef (right)](https://thumb-ap.123doks.com/thumbv2/123dok/3226749.1395844/6.595.61.288.144.230/figure-dimensionality-labelling-dataset-aconstant-neighborhood-optimal-selected.webp)
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