We present a virtual reality (VR) framework to automate the data collection process in cloth folding tasks. The framework uses skeleton representations to help the user define the folding plans for different classes of garments, allowing for replicating the folding on unseen items of the same class. We evaluate the framework in the context of automating garment folding tasks. A quantitative analysis is performed on 3 classes of garments, demonstrating that the framework reduces the need for intervention by the user. We also compare skeleton representations with RGB and binary images in a classification task on a large dataset of clothing items, motivating the use of the framework for other classes of garments.

翻译：我们提出了一种虚拟现实（VR）框架，用于自动化布料折叠任务中的数据采集过程。该框架利用骨架表示来帮助用户定义不同类别服装的折叠方案，从而能够将折叠操作复现至同类未见过物品上。我们围绕服装折叠任务的自动化场景对该框架进行了评估。针对3类服装的定量分析表明，该框架减少了用户干预需求。此外，我们在包含大量服装物品的数据集上，将骨架表示与RGB图像和二值图像在分类任务中进行了对比，论证了该框架可推广至其他类别服装的可行性。