Corner detection of deformable fabric using deep learning
| dc.contributor.author | Mitjans Coma, Albert |
| dc.contributor.author | Maceira Duch, Marc |
| dc.contributor.author | Alenyà Ribas, Guillem |
| dc.contributor.group | Universitat Politècnica de Catalunya. ROBiri - Grup de Percepció i Manipulació Robotitzada de l'IRI |
| dc.contributor.other | Institut de Robòtica i Informàtica Industrial |
| dc.date.accessioned | 2020-04-15T13:40:50Z |
| dc.date.available | 2020-04-15T13:40:50Z |
| dc.date.issued | 2020 |
| dc.description.abstract | Robotic manipulation of deformable objects such as a towel is one of the most challenging tasks in the field of service robotics. Their unpredictable shape and pose makes it difficult to identify the most relevant parts than can be used for grasping. In this report we design a deep neural network that finds all the visible corners of a wrinkled towel. We also create a dataset to train the network. The results obtained show that it is possible to detect the corners of a cloth, but with some constraints due to the small number of images inside the dataset. |
| dc.description.peerreviewed | Peer Reviewed |
| dc.description.version | Preprint |
| dc.format.extent | 18 p. |
| dc.identifier.citation | Mitjans, A.; Maceira, M.; Alenyà, G. "Corner detection of deformable fabric using deep learning". 2020. |
| dc.identifier.uri | https://hdl.handle.net/2117/183478 |
| dc.language.iso | eng |
| dc.relation.ispartofseries | IRI-TR-20-01 |
| dc.rights.access | Open Access |
| dc.rights.licensename | Attribution-NonCommercial-NoDerivs 3.0 Spain |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
| dc.subject | Àrees temàtiques de la UPC::Informàtica::Robòtica |
| dc.subject.inspec | Classificació INSPEC::Pattern recognition::Object detection |
| dc.title | Corner detection of deformable fabric using deep learning |
| dc.type | External research report |
| dspace.entity.type | Publication |
| local.citation.author | Mitjans, A.; Maceira, M.; Alenyà, G. |
| local.identifier.drac | 27008751 |
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