Deformation estimation of industrial objects from a single image
| dc.contributor.advisor | Dubay, Rickey | |
| dc.contributor.advisor | Pickard, Joshua K. | |
| dc.contributor.advisor | Sun, Grace | |
| dc.contributor.author | Eivazi Adli, Sahand | |
| dc.date.accessioned | 2024-11-14T14:47:21Z | |
| dc.date.available | 2024-11-14T14:47:21Z | |
| dc.date.issued | 2024-09 | |
| dc.description.abstract | Deformations introduced during the manufacturing process of plastic components degrade the accuracy of their 3D geometric information, hindering computer vision-based inspection. This phenomenon is prevalent among the primary plastic products where the objects are devoid of texture. This work proposes a solution for the deformation estimation of texture-less plastic objects using only a single RGB image. This solution encompasses a unique image dataset of five deformed parts, including both real-world and synthetic images, a novel method for generating mesh labels, sequential deformation, and a training model based on graph convolution. The sequential deformation method overcomes the prevalent chamfer distance algorithm in generating precise mesh labels. The model achieves a sub-millimeter accuracy on synthetic images and approximately 2.0 mm on real images, with an average testing time of 1.5 s on the Google Colab’s resources. The model’s high precision and speed make it suitable for real-world applications. | |
| dc.description.copyright | © Sahand Eivazi Adli, 2024 | |
| dc.format.extent | xvi, 88 | |
| dc.format.medium | electronic | |
| dc.identifier.uri | https://unbscholar.lib.unb.ca/handle/1882/38190 | |
| dc.language.iso | en | |
| dc.publisher | University of New Brunswick | |
| dc.rights | http://purl.org/coar/access_right/c_abf2 | |
| dc.subject.discipline | Mechanical Engineering | |
| dc.title | Deformation estimation of industrial objects from a single image | |
| dc.type | master thesis | |
| oaire.license.condition | other | |
| thesis.degree.discipline | Mechanical Engineering | |
| thesis.degree.grantor | University of New Brunswick | |
| thesis.degree.level | masters | |
| thesis.degree.name | M.Sc.E. |