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：本文提出一种虚拟现实（VR）框架，用于自动化布料折叠任务中的数据采集过程。该框架采用骨架表示方法辅助用户定义不同种类衣物的折叠方案，从而能够将折叠操作复现于同类未见过衣物上。我们在衣物折叠自动化任务背景下对该框架进行了评估。通过对三类衣物进行定量分析，证明了该框架能够减少用户干预需求。此外，我们在大规模衣物数据集上将骨架表示与RGB图像及二值图像进行了分类任务对比，验证了该框架扩展应用于其他衣物类别的可行性。