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Viewpoint invariant semantic object and scene categorization with RGB-D sensors

Understanding the semantics of objects and scenes using multi-modal RGB-D sensors serves many robotics applications. Key challenges for accurate RGB-D image recognition are the scarcity of training data, variations due to viewpoint changes and the heterogeneous nature of the data. We address these p...

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Bibliographic Details
Main Authors: Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal
Format: Article
Language:English
English
English
Published: Springer New York LLC 2019
Subjects:
Q300 Cybernetics
QA75 Electronic computers. Computer science
Online Access:http://irep.iium.edu.my/64696/20/64696_Viewpoint%20invariant%20semantic%20object%20and%20scene_complete.pdf
http://irep.iium.edu.my/64696/19/64696_Viewpoint%20invariant%20semantic%20object%20and%20scene_scopus.pdf
http://irep.iium.edu.my/64696/31/64696_Viewpoint%20invariant%20semantic%20object%20and%20scene%20categorization%20with%20RGB-D%20sensors_WOS.pdf
http://irep.iium.edu.my/64696/
https://link.springer.com/journal/10514
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http://irep.iium.edu.my/64696/20/64696_Viewpoint%20invariant%20semantic%20object%20and%20scene_complete.pdf
http://irep.iium.edu.my/64696/19/64696_Viewpoint%20invariant%20semantic%20object%20and%20scene_scopus.pdf
http://irep.iium.edu.my/64696/31/64696_Viewpoint%20invariant%20semantic%20object%20and%20scene%20categorization%20with%20RGB-D%20sensors_WOS.pdf
http://irep.iium.edu.my/64696/
https://link.springer.com/journal/10514

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