Caporali, Alessio ;
Galassi, Kevin ;
Zanella, Riccardo ;
Palli, Gianluca
(2023)
REMODEL. WP4. Vision-based Perception. T4_3. Cable Detection and Tracking. Real Time Segmentation of Deformable Linear Objects. v0.
University of Bologna.
DOI
10.6092/unibo/amsacta/7219.
[Dataset]
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Abstract
The dataset contains the source code and model weights utilized for the experimental validation on segmentation of deformable linear objects. The developed approach is called RT-DLO.
A novel method to separate the DLO instances is applied. It employs the generation of a graph representation of the scene given the semantic mask where the graph nodes are sampled from the DLOs center-lines whereas the graph edges are selected based on topological reasoning. RT-DLO also describes each DLO instance with a sequence of 2D coordinates. The associated publication is the following:
A. Caporali, K. Galassi, B. L. Žagar, R. Zanella, G. Palli and A. C. Knoll, "RT-DLO: Real-Time Deformable Linear Objects Instance Segmentation," in IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2023.3245641.
Abstract
The dataset contains the source code and model weights utilized for the experimental validation on segmentation of deformable linear objects. The developed approach is called RT-DLO.
A novel method to separate the DLO instances is applied. It employs the generation of a graph representation of the scene given the semantic mask where the graph nodes are sampled from the DLOs center-lines whereas the graph edges are selected based on topological reasoning. RT-DLO also describes each DLO instance with a sequence of 2D coordinates. The associated publication is the following:
A. Caporali, K. Galassi, B. L. Žagar, R. Zanella, G. Palli and A. C. Knoll, "RT-DLO: Real-Time Deformable Linear Objects Instance Segmentation," in IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2023.3245641.
Document type
Dataset
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Subjects
DOI
Contributors
Deposit date
24 Mar 2023 11:28
Last modified
24 Mar 2023 11:28
Related identifier
Project name
Funding program
EC - H2020
URI
Other metadata
Document type
Dataset
Creators
Subjects
DOI
Contributors
Deposit date
24 Mar 2023 11:28
Last modified
24 Mar 2023 11:28
Related identifier
Project name
Funding program
EC - H2020
URI
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