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Un possibile sviluppo analitico della D.L.T. e sua applicazione per il rilievo dell'architettura
No full textA STATISTICALLY PROVEN AUTOMATIC BASED CLASSIFICATION PROCEDURE OF LASER POINTS
No full textOne of the critical aspects of the curvature based classification of spatial objects from laser point clouds is the correct interpretation
of the results. This is due to the fact that measurements are characterized by errors and that simplified analytical models are applied
to estimate the differential terms used to compute the object surface curvature values. In particular, the differential terms are the first
and second order partial derivatives of a Taylor’s expansion used to determine, by the so-called “Weingarten map” matrix, the
Gaussian and the mean curvatures. Due to the measurement errors and to the simplified model adopted, a statistical procedure is
proposed in this paper. It is based at first on the analysis of variance (ANOVA) carried out to verify the fulfilment of the second
order Taylor’s expansion applied to locally compute the curvature differential terms. Successively, the variance covariance
propagation law is applied to the estimated differential terms in order to calculate the variance covariance matrix of a two rows
vector containing the Gaussian and the mean curvature estimates. An F ratio test is then applied to verify the significance of the
Gaussian and of the mean curvature values. By analysing the test acceptance or rejection for K and H, and their sign, a reliable
classification of the whole point cloud into its geometrical basic types is carried out. Some numerical experiments on synthetic and
real laser data finally emphasize the capabilities of the method proposed
Automatic modeling of laser point clouds by statistical analysis of surface curvature values
No full textLaser scanning measurements are characterized by errors of different kind and simplified analytical models are normally applied to estimate the differential terms used to locally compute the object surface curvature values. The paper synthesizes the statistical analyses of the non parametric model applied, and of the Gaussian K and mean H local curvatures values, as already proposed by
the authors in recent papers. The statistical analyses are based at first on a Chi-Square test applied to verify the second order Taylor’s expansion model fulfilment. Afterwards, the variance-covariance propagation law is applied to the estimated differential terms to calculate the covariance matrix of a vector containing the Gaussian and the mean curvature estimates and an F ratio test is applied to verify their significance. By analyzing the test results for K and H, and their sign, a reliable classification of the whole point cloud into its geometrical basic types is carried out. To perform the units segmentation, by analytically detecting discontinuity lines, an analysis of the extended Taylor’s model to the third and fourth order terms is mentioned. Some numerical experiments on real noisy laser data relating to a complex surface of a church apse confirm the validity of the method proposed
Elaborazione di foto d’archivio per il rilievo fotogrammetrico di edifici distrutti dal terremoto: l’esempio del Castello di Gemona del Friuli.
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Filtraggio di dati laser altimetrici con modelli autoregressivi SAR ed algoritmi di ricerca dinamica BFS (Block Forward Search)
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A segmentation procedure of LIDaR data by applying mixed parametric and nonparametric models
No full textLaser scanning survey of the Aquileia Basilica (Italy) and automatic modeling of the volumetric primitives
No full textThe paper deals with the terrestrial laser scanning survey of the Aquileia basilica, one of the most significant monuments of the
Italian Romanic architecture, the religious centre of a small town in North-East Italy famous for its roman archaeological ruins. The laser data have been acquired with a Riegl LMS Z360i system integrated with a Nikon D100 metric camera, while the data
processing has been carried out by the RiSCAN PRO software. The survey consists of 28 scans and 138 digital images for the internal aisles, and 14 scans and 55 digital images for the front external walls and the 73 m high bell tower. Thanks to 53 reflecting targets, surveyed from a GPS point network, the scans have been registered and geo-referenced in the Italian national cartographic
system. An aerial laser survey of the whole Aquileia area, carried out with an Optech system, was yet available in the same datum.
In this way, a very detailed 3D model has been reached for such a very complex architectonic monument: by suitably exploiting the
software tools, a large number of numerical products have been automatically obtained, as coloured point clouds, TIN surfaces, vector sections, image texturing and orthophoto, as well as very realistic virtual navigations among them. For the automatic modeling of some main volumetric primitives, a three steps procedure, recently proposed by the authors, has been applied. By a nonparametric second order Taylor’s expansion, the values of the 3D surface function, and the first and second order partial derivatives are locally estimated. From these, the elements of the so-called “Weingarten map” matrix are computed, and from
the latter, the values of the gaussian and mean curvatures are finally evaluated. According to these values, the points are classified
into four basic types (hyperbolic, parabolic, planar, and elliptic); after that, a region growing method allows a first raw segmentation. At last, a parametric regression for each raw cluster and a restricted surrounding buffer area is iteratively applied.
The automatic modeling procedure has been applied to the basilica main apse. The obtained results seem to be very promising: the
procedure has correctly classified the bottom parabolic part, the planes close to the windows and the top elliptical part
Algoritmi di segmentazione e vettorializzazione per il rilievo laser aereo dell’edificato urbano
No full textThis paper presents two original automatic algorithms for the point segmentation and vectorization of a laser scanning survey of urban buildings. The segmentation algorithm is composed of two
sequential phases: in the first one a nonparametric regression model is applied to identify the initial
clusters of geometrically and topologically homogeneous points. To each cluster, a parametric model is successively applied to obtain a high reliable roof plane segmentation. The vectorization algorithm is able to distinguish and correctly reconstruct internal and border lines of a roof. By applying the two algorithms to high frequency laser survey data, a reliable vectorial solid modelling of buildings has been automatically obtained
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