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Object Detection in Point Clouds Based on 2D Images

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F20%3A00344477" target="_blank" >RIV/68407700:21220/20:00344477 - isvavai.cz</a>

  • Result on the web

    <a href="https://aleph.cvut.cz/" target="_blank" >https://aleph.cvut.cz/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Object Detection in Point Clouds Based on 2D Images

  • Original language description

    Point clouds are becoming a much more popular topic in computer vision, mainly because of the added information about distance in 3D space. Due to this advantage, point clouds are frequently used in autonomous driving, digital terrain modeling, precise measuring, etc... Nevertheless, point clouds are much more complicated than images for basic computer vision tasks. This paper contains a review of the basic algorithms of point cloud segmentation methods and provides a derived algorithm for object detection based on 2D views which are created directly from point cloud.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    28th WORKSHOP OF APPLIED MECHANICS BOOK OF PAPERS

  • ISBN

    978-80-01-06791-8

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    30-33

  • Publisher name

    České vysoké učení technické v Praze

  • Place of publication

    Praha

  • Event location

    online

  • Event date

    Nov 27, 2020

  • Type of event by nationality

    CST - Celostátní akce

  • UT code for WoS article