Activities of Daily Living Object Dataset

Name: Activities of Daily Living Object Dataset
Creator: figshare
Published: 2024-11-28 16:29:30
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DataCite Commons2024-11-28 更新2025-01-06 收录

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ADL (Activities of Daily Living) Object DatasetOverviewThe ADL (Activities of Daily Living) Object Dataset is a curated collection of images and annotations specifically focusing on objects commonly interacted with during daily living activities. This dataset is designed to facilitate research and development in assistive robotics in home environments.Data Sources and LicensingThe dataset comprises images and annotations sourced from four publicly available datasets:COCO DatasetLicense: Creative Commons Attribution 4.0 International (CC BY 4.0)License Link: https://creativecommons.org/licenses/by/4.0/Citation:Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014). Microsoft COCO: Common Objects in Context. European Conference on Computer Vision (ECCV), 740–755.Open Images DatasetLicense: Creative Commons Attribution 4.0 International (CC BY 4.0)License Link: https://creativecommons.org/licenses/by/4.0/Citation:Kuznetsova, A., Rom, H., Alldrin, N., Uijlings, J., Krasin, I., Pont-Tuset, J., Kamali, S., Popov, S., Malloci, M., Duerig, T., & Ferrari, V. (2020). The Open Images Dataset V6: Unified Image Classification, Object Detection, and Visual Relationship Detection at Scale. International Journal of Computer Vision, 128(7), 1956–1981.LVIS DatasetLicense: Creative Commons Attribution 4.0 International (CC BY 4.0)License Link: https://creativecommons.org/licenses/by/4.0/Citation:Gupta, A., Dollar, P., & Girshick, R. (2019). LVIS: A Dataset for Large Vocabulary Instance Segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5356–5364.Roboflow UniverseLicense: Creative Commons Attribution 4.0 International (CC BY 4.0)License Link: https://creativecommons.org/licenses/by/4.0/Citation:Roboflow Universe: Open Source Computer Vision Community. (2024, October 18). Retrieved from https://universe.roboflow.comAll images and annotations obtained from these datasets are released under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits sharing and adaptation of the material in any medium or format, for any purpose, even commercially, provided that appropriate credit is given, a link to the license is provided, and any changes made are indicated.Redistribution Permission:As all images and annotations are under the CC BY 4.0 license, we are legally permitted to redistribute this data within our dataset. We have complied with the license terms by:Providing appropriate attribution to the original creators.Including links to the CC BY 4.0 license.Indicating any changes made to the original material.Dataset StructureThe dataset includes:Images: High-quality images featuring ADL objects suitable for robotic manipulation.Annotations: Bounding boxes and class labels formatted in the YOLO (You Only Look Once) Darknet format.ClassesThe dataset focuses on objects commonly involved in daily living activities. A full list of object classes is provided in the <code>classes.txt</code> file.FormatImages: JPEG format.Annotations: Text files corresponding to each image, containing bounding box coordinates and class labels in YOLO Darknet format.How to Use the DatasetDownload the DatasetUnpack the Dataset <pre><pre>unzip ADL_Object_Dataset.zip </pre></pre>How to Cite This DatasetIf you use this dataset in your research, please cite our paper:<pre><pre>@article{shahria2024adl, title={Activities of Daily Living Object Dataset: Advancing Assistive Robotic Manipulation with a Tailored Dataset}, author={Shahria, Md Tanzil and Rahman, Mohammad H}, journal={Sensors}, year={2024}, publisher={MDPI} } </pre></pre>LicenseThis dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).License Link: https://creativecommons.org/licenses/by/4.0/By using this dataset, you agree to provide appropriate credit, indicate if changes were made, and not impose additional restrictions beyond those of the original licenses.AcknowledgmentsWe gratefully acknowledge the use of data from the following open-source datasets, which were instrumental in the creation of our specialized ADL object dataset:COCO Dataset: We thank the creators and contributors of the COCO dataset for making their images and annotations publicly available under the CC BY 4.0 license.Open Images Dataset: We express our gratitude to the Open Images team for providing a comprehensive dataset of annotated images under the CC BY 4.0 license.LVIS Dataset: We appreciate the efforts of the LVIS dataset creators for releasing their extensive dataset under the CC BY 4.0 license.Roboflow Universe: We acknowledge the Roboflow Universe community for sharing their datasets under the CC BY 4.0 license.Their contributions have been invaluable to our research, and we thank them for their commitment to open science and data sharing.Usage GuidelinesThis dataset is intended for research and educational purposes.Users must comply with the licenses of the source datasets.Redistribution of the dataset should include this README file and maintain the same license.Contact InformationMd Tanzil ShahriaEmail: mshahria@uwm.edu; tanzilshahria@gmail.com.Institution: University of Wisconsin-MilwaukeeDisclaimerWhile we have taken care to ensure full compliance with all licensing terms, users are responsible for ensuring their own compliance when using the dataset.

ADL（日常生活活动，Activities of Daily Living）对象数据集概述 ADL（日常生活活动，Activities of Daily Living）对象数据集是一个精心整理的图像和注释集合，专门聚焦于日常生活活动中常见的交互对象。该数据集旨在促进家庭环境下辅助机器人技术的研发。数据来源与许可数据集包含来自四个公开可用数据集的图像和注释： COCO数据集 许可：知识共享署名4.0国际许可协议（CC BY 4.0） 许可链接：https://creativecommons.org/licenses/by/4.0/ 引用：Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014). 《微软COCO：上下文通用对象》. 欧洲计算机视觉会议（ECCV）, 740–755. Open Images数据集 许可：知识共享署名4.0国际许可协议（CC BY 4.0） 许可链接：https://creativecommons.org/licenses/by/4.0/ 引用：Kuznetsova, A., Rom, H., Alldrin, N., Uijlings, J., Krasin, I., Pont-Tuset, J., Kamali, S., Popov, S., Malloci, M., Duerig, T., & Ferrari, V. (2020). 《Open Images数据集V6：大规模统一图像分类、对象检测与视觉关系检测》. 国际计算机视觉杂志, 128(7), 1956–1981. LVIS数据集 许可：知识共享署名4.0国际许可协议（CC BY 4.0） 许可链接：https://creativecommons.org/licenses/by/4.0/ 引用：Gupta, A., Dollar, P., & Girshick, R. (2019). 《LVIS：大词汇量实例分割数据集》. 美国电气和电子工程师协会计算机视觉与模式识别会议（CVPR）论文集, 5356–5364. Roboflow Universe 许可：知识共享署名4.0国际许可协议（CC BY 4.0） 许可链接：https://creativecommons.org/licenses/by/4.0/ 引用：Roboflow Universe: Open Source Computer Vision Community. (2024, October 18). 检索自 https://universe.roboflow.com 所有从这些数据集获取的图像和注释均在知识共享署名4.0国际许可协议（CC BY 4.0）下发布。该许可允许以任何媒介或格式共享和改编材料，用于任何目的（包括商业用途），但需满足以下条件：给予适当的归属、提供许可链接，并指明所做的任何修改。 重新分发许可： 由于所有图像和注释均遵循CC BY 4.0许可，我们在法律上有权在本数据集中重新分发这些数据。我们已通过以下方式遵守许可条款： - 向原始创作者提供适当的归属。 - 包含CC BY 4.0许可的链接。 - 指明对原始材料所做的任何修改。数据集结构数据集包含： 图像：包含适合机器人操作的ADL对象的高质量图像。 注释：采用YOLO（You Only Look Once）Darknet格式的边界框和类别标签。类别数据集聚焦于日常生活活动中常见的对象。完整的对象类别列表见<code>classes.txt</code>文件。格式 图像：JPEG格式。 注释：与每个图像对应的文本文件，包含YOLO Darknet格式的边界框坐标和类别标签。如何使用数据集 下载数据集 解压数据集 <pre><pre>unzip ADL_Object_Dataset.zip </pre></pre> 如何引用本数据集如果您在研究中使用本数据集，请引用我们的论文： <pre><pre>@article{shahria2024adl, title={Activities of Daily Living Object Dataset: Advancing Assistive Robotic Manipulation with a Tailored Dataset}, author={Shahria, Md Tanzil and Rahman, Mohammad H}, journal={Sensors}, year={2024}, publisher={MDPI} } </pre></pre> 许可本数据集在知识共享署名4.0国际许可协议（CC BY 4.0）下发布。 许可链接：https://creativecommons.org/licenses/by/4.0/ 使用本数据集即表示您同意给予适当的归属、指明是否有修改，并不施加超出原始许可范围的额外限制。致谢我们衷心感谢以下开源数据集的数据使用，它们对我们专业ADL对象数据集的创建至关重要： COCO数据集：感谢COCO数据集的创建者和贡献者，他们在CC BY 4.0许可下公开了其图像和注释。 Open Images数据集：感谢Open Images团队在CC BY 4.0许可下提供了全面的带注释图像数据集。 LVIS数据集：感谢LVIS数据集的创建者在CC BY 4.0许可下发布了其广泛的数据集。 Roboflow Universe：感谢Roboflow Universe社区在CC BY 4.0许可下共享其数据集。他们的贡献对我们的研究无价，我们感谢他们对开放科学和数据共享的承诺。使用指南 - 本数据集仅供研究和教育目的使用。 - 用户必须遵守源数据集的许可条款。 - 重新分发数据集时应包含本README文件，并保持相同的许可。联系信息 Md Tanzil Shahria 邮箱：mshahria@uwm.edu; tanzilshahria@gmail.com 机构：威斯康星大学密尔沃基分校免责声明尽管我们已尽力确保完全遵守所有许可条款，但用户在使用数据集时需自行负责确保合规性。

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