Journal article Open Access
Akash Kuamr Ghanate; Aashish M; Santhosh M Patil, Sowmyarani C N; Sowmyarani C N; Ramakanth Kumar P
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nam##2200000uu#4500</leader> <datafield tag="041" ind1=" " ind2=" "> <subfield code="a">eng</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">3D Mapping, JSNet, Segmentation, SLAM, Sfm, PointNet</subfield> </datafield> <controlfield tag="005">20210927134823.0</controlfield> <controlfield tag="001">5529579</controlfield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">B.E., Department of Computer Science and Engineering, R.V College of Engineering, Bangalore, India.</subfield> <subfield code="a">Aashish M</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">B.E., Department of Computer Science and Engineering, R.V College of Engineering, Bangalore, India.</subfield> <subfield code="a">Santhosh M Patil, Sowmyarani C N</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">Associate Professor, Department of Computer Science and Engineering, R.V College of Engineering, Bangalore, India.</subfield> <subfield code="a">Sowmyarani C N</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">Professor & HoD, Department of Computer Science and Engineering, R.V College of Engineering, Bangalore, India</subfield> <subfield code="a">Ramakanth Kumar P</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">Publisher</subfield> <subfield code="4">spn</subfield> <subfield code="a">Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">734689</subfield> <subfield code="z">md5:a9dfa61e2e93f3331e34119dc7358565</subfield> <subfield code="u">https://zenodo.org/record/5529579/files/E1020069520.pdf</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2020-08-30</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="p">openaire</subfield> <subfield code="o">oai:zenodo.org:5529579</subfield> </datafield> <datafield tag="909" ind1="C" ind2="4"> <subfield code="c">22-29</subfield> <subfield code="n">6</subfield> <subfield code="p">International Journal of Engineering and Advanced Technology (IJEAT)</subfield> <subfield code="v">9</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="u">B.E., Department of Computer Science and Engineering, R.V College of Engineering, Bangalore, India.</subfield> <subfield code="a">Akash Kuamr Ghanate</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">Review on 3D Mapping and Segmentation</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="u">https://creativecommons.org/licenses/by/4.0/legalcode</subfield> <subfield code="a">Creative Commons Attribution 4.0 International</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="a">cc-by</subfield> <subfield code="2">opendefinition.org</subfield> </datafield> <datafield tag="650" ind1="1" ind2=" "> <subfield code="a">ISSN</subfield> <subfield code="0">(issn)2249-8958</subfield> </datafield> <datafield tag="650" ind1="1" ind2=" "> <subfield code="a">Retrieval Number</subfield> <subfield code="0">(handle)E1020069520/2020©BEIESP</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><p>The deployment of a robot in a remote environment is a field of research that has huge applications. The robotic system must have the capability of sensing its surroundings and being aware of what it is around. We concluded two key tasks for this purpose, which are 3D mapping and segmentation. This paper shows a comprehensive review of the different 3D mapping and segmentation methods. Mapping techniques include those using RGB images, RGBD images and LIDAR. Segmentation techniques include PointNet, PointNet++, 3D semantic and instance segmentation and joint instance segmentation. We also describe two end-to-end approaches for mapping and segmentation. These methods are reviewed elaborately, comparisons are drawn between them, challenges are presented and future directions in addressing these challenges are pointed out.</p></subfield> </datafield> <datafield tag="773" ind1=" " ind2=" "> <subfield code="n">issn</subfield> <subfield code="i">isCitedBy</subfield> <subfield code="a">2249-8958</subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.35940/ijeat.E1020.089620</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">publication</subfield> <subfield code="b">article</subfield> </datafield> </record>
Views | 42 |
Downloads | 31 |
Data volume | 22.8 MB |
Unique views | 42 |
Unique downloads | 30 |