Research on Occluded Objects 6DoF Pose Estimation with Multi-feature and Pixel- level Fusion Article Swipe
In order to solve the problem that current robots are difficult to achieve accurate 6DoF pose estimation under the environment of occluded objects and insufficient lighting, in this paper, a pixel-level based neural network framework is proposed, which includes three modules, the RGB feature extraction networks module, the pixel-level fusion module and the 6D pose regression network module. The RGB feature extraction networks module firstly segments the target objects and then extracts the objects?? features. The pixel-level fusion module is applied for fusing RGB features with 3D multi-view features. And the last module fuses 3D point cloud pixels and outputs the 6D pose of the objects. The experiments conducted on the YCB-Video dataset, the LINEMOD dataset, and the YCB-Occlusion dataset processed in this paper manifest that the framework proposed can effectively predict the 6D pose of the objects even when the objects are occluded or the point clouds of the object are lost. Furthermore, compared with other frameworks, this framework is more robust and the efficiency is improved by hundreds of times only with a small loss of accuracy.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doaj.org/article/65979c7c10db4497876cdceb001c6998
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390253258
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4390253258Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3778/j.issn.1673-9418.2003041Digital Object Identifier
- Title
-
Research on Occluded Objects 6DoF Pose Estimation with Multi-feature and Pixel- level FusionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-12-01Full publication date if available
- Authors
-
Dayong ChenList of authors in order
- Landing page
-
https://doaj.org/article/65979c7c10db4497876cdceb001c6998Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doaj.org/article/65979c7c10db4497876cdceb001c6998Direct OA link when available
- Concepts
-
Artificial intelligence, Computer vision, Pose, Feature (linguistics), Computer science, Pixel, Fusion, Pattern recognition (psychology), Estimation, Engineering, Linguistics, Philosophy, Systems engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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