From a progressive planarity-driven coarsening of the input data, we demonstrate that we can reliably detect structural scales whose characteristics are learned ...

We present a framework to automatically extract a set of representations that capture the shape and structure of man-made objects at different key Abstraction ...

Shape detection from raw 3D data is a long-standing problem whose goal consists in turning a large amount of geometric data into a higher level representation ...

We present a framework to automatically extract a set of representations that capture the shape and structure of man-made objects at different key Abstraction ...

This work presents a framework to automatically extract a set of representations that capture the shape and structure of man-made objects at different key ...

It is capable of accurately representing piecewise planar structures while also approximating freeform objects from incomplete geometric structures. Fang et al.

Jun 1, 2022 · In this paper, we use two Convolutional Neural Networks (CNNs) to respectively identify the symmetry group and symmetry order of planar engineering structures.

In order to account for rotation, scaling and translation of the shape, more parameters must be added to the parameter space which makes the implementation ...

Oct 22, 2024 · A technique for detecting and localizing corners of planar curves is proposed. The technique is based on Gaussian scale space, ...

We present a method for planar shape detection and regularization from raw point sets. The geometric modelling and processing of man-made environments