Surface Reconstruction Using Adaptive Clustering Methods

نویسندگان

  • Bjørn Heckel
  • Antonio E. Uva
  • Bernd Hamann
  • Kenneth I. Joy
چکیده

We present an automatic method for the generation of surface triangulations from sets of scattered points. Given a set of scattered points in three-dimensional space, without connectivity information, our method reconstructs a triangulated surface model in a two-step procedure. First, we apply an adaptive clustering technique to the given set of points, identifying point subsets in regions that are nearly planar. The output of this clustering step is a set of two-manifold “tiles” that locally approximate the underlying, unknown surface. Second, we construct a surface triangulation by triangulating the data within the individual tiles and the gaps between the tiles. This algorithm can generate multiresolution representations by applying the triangulation step to various resolution levels resulting from the hierarchical clustering step. We compute deviation measures for each cluster, and thus we can produce reconstructions with prescribed error bounds.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Block-Based Compressive Sensing Using Soft Thresholding of Adaptive Transform Coefficients

Compressive sampling (CS) is a new technique for simultaneous sampling and compression of signals in which the sampling rate can be very small under certain conditions. Due to the limited number of samples, image reconstruction based on CS samples is a challenging task. Most of the existing CS image reconstruction methods have a high computational complexity as they are applied on the entire im...

متن کامل

Prediction of slope stability using adaptive neuro-fuzzy inference system based on clustering methods

Slope stability analysis is an enduring research topic in the engineering and academic sectors. Accurate prediction of the factor of safety (FOS) of slopes, their stability, and their performance is not an easy task. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was utilized to build an estimation model for the prediction of FOS. Three ANFIS models were implemented including g...

متن کامل

INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES

The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...

متن کامل

Application of artificial intelligence methods for estimation of maximum surface settlement caused by EPB shield tunneling

Maximum surface settlement (MSS) is an important parameter for the design and operation of earth pressure balance (EPB) shields that should determine before operate tunneling. Artificial intelligence (AI) methods are accepted as a technology that offers an alternative way to tackle highly complex problems that can’t be modeled in mathematics. They can learn from examples and they are able...

متن کامل

Organ Surface Reconstruction using B-Splines and Hu Moments

The following article presents a combination of image processing and computer graphics methods which form an algorithm for 3D surface reconstruction of inner organs imaged using Computed Tomography. The presented method uses k-means clustering and Hu moments to filter desired contours from a large number detected in CT frames. Leastsquares B-spline fitting is used to approximate the filtered co...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1999