We present a new method for extracting features of a 3D object targeted to CAD modeling directly from the point cloud of its surface scan. The objective is to obtain an editable CAD model that is manufacturable and describes accurately the structure and topology of the point cloud. The entire process is carried out with the least human intervention possible. First, the point cloud is sliced int...

The cloud-point methodology was successfully employed for the preconcentration of heavy metal cations at trace levels from aqueous samples prior to flame atomic absorption spectrometry (FAAS). Cations were taken into a complex with 8-quinolinol in an aqueous non-ionic surfactant, Triton X-114, medium and concentrated in the surfactant rich phase by bringing the solution to the cloud-point tempe...

a simple and sensitive method is described for the pre-concentration by cloud point extraction followed by atomic absorption spectrometric determination of copper ion in real samples. at a solution ph of 5.5, 5, 5-diphenylimidazolidine-2, 4-dione (phenytoin) (dfid) and tritonx-114 were used as hydrophobic ligand and non-ionic surfactant. the adopted concentrations for dfid, triton x-114 and hno...

This paper presents SO-Net, a permutation invariant architecture for deep learning with orderless point clouds. The SO-Net models the spatial distribution of point cloud by building a Self-Organizing Map (SOM). Based on the SOM, SO-Net performs hierarchical feature extraction on individual points and SOM nodes, and ultimately represents the input point cloud by a single feature vector. The rece...

The quick and accurate understanding of the ambient environment, which is composed of road curbs, vehicles, pedestrians, etc., is critical for developing intelligent vehicles. The road elements included in this work are road curbs and dynamic road obstacles that directly affect the drivable area. A framework for the online modeling of the driving environment using a multi-beam LIDAR, i.e., a Ve...

This paper presents algorithms for fast segmentation of 3D point clouds and subsequent classification of the obtained 3D segments. The method jointly determines the ground surface and segments individual objects in 3D, including overhanging structures. When compared to six other terrain modelling techniques, this approach has minimal error between the sensed data and the representation; and is ...