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Related Concept Videos

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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A neutral atom consists of a positively charged nucleus surrounded by a negatively charged electron cloud. When placed in an external electric field, the external electric force pulls the electrons and nucleus apart, opposite to the intrinsic attraction between the nucleus and the electrons. The opposing forces balance each other with a slight shift between the center of masses of the nucleus and the electron cloud, resulting in a polarized atom. On the other hand, a few molecules, like water,...
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Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
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Novel Adaptive Laser Scanning Method for Point Clouds of Free-Form Objects.

Yufu Zang1, Bisheng Yang2, Fuxun Liang3

  • 1School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China. 3dmapzangyufu@nuist.edu.cn.

Sensors (Basel, Switzerland)
|July 13, 2018
PubMed
Summary

This study introduces a multi-level simplification method for optimizing laser-scanned point clouds of 3D objects. It adaptively selects optimal points to reduce data while preserving geometric detail for free-form objects.

Keywords:
adaptive representationgeometric multi-levelperceptual qualityradial basis functionsurface variation

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Area of Science:

  • Computer Vision
  • Geometric Modeling
  • 3D Scanning Technology

Background:

  • Laser scanners generate 3D point clouds of objects.
  • Point cloud optimization is crucial for solid model creation and data transfer.
  • Existing methods struggle with multi-level detail representation.

Purpose of the Study:

  • To develop an adaptive multi-level simplification method for 3D point clouds.
  • To optimize point cloud data while preserving geometric information.
  • To address limitations of single-level detail extraction.

Main Methods:

  • A multi-level simplification strategy is proposed.
  • Point importance is measured by local surface variation and neighboring point distribution.
  • Perceptual quality degradation is evaluated using adjusted mesh structural distortion.

Main Results:

  • The method adaptively determines the optimal level of points for simplification.
  • It effectively reduces point cloud size while maintaining geometric accuracy.
  • Experimental results demonstrate reliable optimization for free-form objects.

Conclusions:

  • The proposed multi-level strategy offers a robust solution for point cloud optimization.
  • This method enhances adaptive laser scanning of complex 3D objects.
  • It provides a reliable way to manage geometric data from 3D scans.