A parallel memory efficient outlier detection algorithm for large unstructured point clouds

2021 ◽  
Author(s):  
Daniel Sopauschke ◽  
Christian Teutsch ◽  
Erik Trostmann ◽  
Dirk Berndt
Keyword(s):  
Outlier Detection ◽  
Point Clouds ◽  
Detection Algorithm ◽  
Parallel Memory ◽  
Memory Efficient

scholarly journals RODA: A Fast Outlier Detection Algorithm Supporting Multi-Queries

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 43271-43284
Author(s):  
Xite Wang ◽  
Jiafan Li ◽  
Mei Bai ◽  
Qian Ma
Keyword(s):  
Outlier Detection ◽  
Detection Algorithm

Research on the framework of university ideological and political education management system based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Political Theory ◽  
Outlier Detection ◽  
Management System ◽  
Detection Algorithm ◽  
Colleges And Universities ◽  
Ideological And Political Education ◽  
Political Education ◽  
Data Simulation ◽  
Artificial Intelligence Technology

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

Extracting Geometric Edges from 3D Point Clouds Based on Normal Vector Change

2014 ◽  
Vol 571-572 ◽  
pp. 729-734
Author(s):  
Jia Li ◽  
Huan Lin ◽  
Duo Qiang Zhang ◽  
Xiao Lu Xue
Keyword(s):  
Point Clouds ◽  
Detection Algorithm ◽  
Growth Strategy ◽  
Normal Vector ◽  
Geometric Morphometric ◽  
3D Point Clouds ◽  
Real Scene ◽  
Edge Points ◽  
Normal Vectors ◽  
Change Intensity

Normal vector of 3D surface is important differential geometric property over localized neighborhood, and its abrupt change along the surface directly reflects the variation of geometric morphometric. Based on this observation, this paper presents a novel edge detection algorithm in 3D point clouds, which utilizes the change intensity and change direction of adjacent normal vectors and is composed of three steps. First, a two-dimensional grid is constructed according to the inherent data acquisition sequence so as to build up the topology of points. Second, by this topological structure preliminary edge points are retrieved, and the potential directions of edges passing through them are estimated according to the change of normal vectors between adjacent points. Finally, an edge growth strategy is designed to regain the missing edge points and connect them into complete edge lines. The results of experiment in a real scene demonstrate that the proposed algorithm can extract geometric edges from 3D point clouds robustly, and is able to reduce edge quality’s dependence on user defined parameters.

scholarly journals Use of geotechnologies in mining planning in Quarries carbonated rocks - Contribution to the digital transition (Industry 4.0)

2021 ◽  
Vol 906 (1) ◽  
pp. 012015
Author(s):  
João Duarte ◽  
Francisco Sousa ◽  
Bruno Valente
Keyword(s):  
Industry 4.0 ◽  
Economic Valuation ◽  
Reference Value ◽  
Point Clouds ◽  
Detection Algorithm ◽  
Second Phase ◽  
Ornamental Stone ◽  
Use Of Resources ◽  
Photogrammetric Method

Abstract As part of the strategy for Industry 4.0, this work was developed to outline a methodology that is an important contribution to improve the efficiency and productivity of processes in the ornamental stone extraction industry. Since this sector is important for the Portuguese economy, it is imperative to optimize processes to improve their efficiency in the use of resources, economic valuation, and economic viability. Knowing that one of the main factors to take into account in the feasibility of an exploration of ornamental rocks is the density, persistence and attitude of the discontinuities present in the rock mass, a methodology is proposed that aims to map and characterize the existing discontinuities in the using the latest digital technologies and whenever possible open access (CloudCompare, Stereonet, 3D Block Expert). To this end, work was initially carried out on an active exploration front, identifying and characterizing, through the traditional method (compass and clinometer) and photogrammetry, existing discontinuities and statistically analysing their occurrence. The data analysis shows a variation in the attitude of the discontinuities in a range of -17.72 ° to 14.7 °, this variation corresponding to the strike. As a percentage, there is also a variation in the range of values, from -5.30% to 4.91%, with the reference value being the value obtained by the photogrammetric method. This step was also used to compare the acquired data and verify the variations between them depending on the method used. Photogrammetry was used with another complementary purpose, but very important for the proposed methodology, which is related to the 3D modelling of the fronts and the subsequent projection or extraction of the existing discontinuity plans. The determination of the attitude of the discontinuities was obtained through the manipulation of the point clouds obtained by the photogrammetric modelling, based on the technique of Structure for Motion [SfM] and application of the RANSAC Shape Detection algorithm of the CloudCompare® program, which allows the determination of the attitude of the discontinuities. The characterization of the discontinuities by the photogrammetric method provided the data that was used in the present study to calculate the blocometry in that sector. This was calculated using the 3D BlockExpert software, based on the exploration sequences. The program calculated the predicted volumes in each one, based on a standard dimension for the block of 2.7 × 3.0 × 2.0 meters. As a result, it was possible to compare a number of blocks the value predicted by the 449 modellings and the number of blocks produced 490. This difference of approximately 10% for this order of magnitude is acceptable and confirms the reliability of the proposed methodology. This evaluation using Geotechnologies allows data modelling to be effectively an important process in the planning of the extractive process, and with the development of this approach, it may introduce in a second phase the decision automation of the extractive process, based on economic and commercial criteria and last and third stage, the automation of the extractive process.

Sign in / Sign up

Export Citation Format

Share Document