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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English English |
| Published: |
Springer New York LLC
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/64696/ http://irep.iium.edu.my/64696/ http://irep.iium.edu.my/64696/ 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 |
Internet
http://irep.iium.edu.my/64696/http://irep.iium.edu.my/64696/
http://irep.iium.edu.my/64696/
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