3D point cloud analysis
In this paper, I propose a novel idea to tackle the 3D Point Cloud Object Detection and Segmentation research topic called Transfer Fusion. It will be used in tandem with M2Track and I will also be exploring the differences between M2Track as a standalone versus with TF. M2Tracks uses a motion-centr...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/163348 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In this paper, I propose a novel idea to tackle the 3D Point Cloud Object Detection and Segmentation research topic called Transfer Fusion. It will be used in tandem with M2Track and I will also be exploring the differences between M2Track as a standalone versus with TF. M2Tracks uses a motion-centric paradigm as the main focus to get the results. Whereas Transfer Fusion, relies on overlapping data from 2 different sources to obtain depth perception and additional information that may assist in the boosting of the accuracy and precision rates. Additionally, I will highlight the differences, create hypothesis from the results and also provide the grounds for further research to be done in this field. |
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