ICRA 2024poster0 citations

Introducing CEA-IMSOLD: an Industrial Multi-Scale Object Localization Dataset

Boris Meden, Pablo Vega, Fabrice Mayran De Chamisso, Steve Bourgeois

Abstract

We introduce the CEA Industrial Multi-Scale Object Localization Dataset (CEA-IMSOLD), a new BOP format dataset for 6-DoF object localization, crucial for robotics. This dataset aims to evaluate the current localization methods with respect to a new difficulty: large variations in observation distance and, consequently, large variations in image appearance. Compared to the other publicly available datasets, our dataset provides both images with objects small and completely visible in the image, and images where objects are observed close enough so they appear larger than the field of view of the camera. We also propose to consider the observation distance in the evaluation process and introduce new metrics to do so. Finally, our dataset contains a large variety of industrial objects, from small and simple objects such as bolts to sizable and complex ones such as large car parts. We provide baseline results and the dataset is made publicly available to support the community at https://cea-list.github.io/CEA-IMSOLD/.

BibTeX
@inproceedings{icra2024_introducingceaim,
  title = {Introducing CEA-IMSOLD: an Industrial Multi-Scale Object Localization Dataset},
  author = {Boris Meden and Pablo Vega and Fabrice Mayran De Chamisso and Steve Bourgeois},
  booktitle = {ICRA 2024},
  year = {2024}
}
Introducing CEA-IMSOLD: an Industrial Multi-Scale Object Localization Dataset · ICRA 2024