Browsing by Author "Eivazi Adli, Sahand"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Deformation estimation of industrial objects from a single image
    (University of New Brunswick, 2024-09) Eivazi Adli, Sahand; Dubay, Rickey; Pickard, Joshua K.; Sun, Grace
    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.