DIO: Dataset of 3D Mesh Models of Indoor Objects for Robotics and
  Computer Vision Applications
Nillan Nimal Wenbin Li Ronald Clark Sajad Saeedi
The creation of accurate virtual models of real-world objects is imperative
to robotic simulations and applications such as computer vision, artificial
intelligence, and machine learning. This paper documents the different methods
employed for generating a database of mesh models of real-world objects. These
methods address the tedious and time-intensive process of manually generating
the models using CAD software. Essentially, DSLR/phone cameras were employed to
acquire images of target objects. These images were processed using a
photogrammetry software known as Meshroom to generate a dense surface
reconstruction of the scene. The result produced by Meshroom was edited and
simplified using MeshLab, a mesh-editing software to produce the final model.
Based on the obtained models, this process was effective in modelling the
geometry and texture of real-world objects with high fidelity. An active 3D
scanner was also utilized to accelerate the process for large objects. All
generated models and captured images are made available on the website of the
project.