Data underlying the publication- SENS3: Multisensory Database of Finger-Surface Interactions and Corresponding Sensations
收藏DataCite Commons2024-07-10 更新2024-07-13 收录
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https://data.4tu.nl/datasets/e7f8f6dd-b61c-42fc-bea9-5ff103cbe396/1
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The growing demand for natural interactions with technology underscores the importance of achieving realistic touch sensations in digital environments. Realizing this goal highly depends on comprehensive databases of finger-surface interactions, which need further development. Here, we present SENS3—www.sens3.net— an extensive open-access repository of multisensory data acquired from fifty surfaces when two participants explored them with their fingertips through static contact, pressing, tapping, and sliding. SENS3 encompasses high-fidelity visual, audio, and haptic information recorded during these interactions, including videos, sounds, contact forces, torques, positions, accelerations, skin temperature, heat flux, and surface photographs. Additionally, it incorporates thirteen participants’ psychophysical sensation ratings (rough–smooth, flat–bumpy, sticky–slippery, hot–cold, regular–irregular, fine–coarse, hard–soft, and wet–dry) while exploring these surfaces freely. Designed with an open-ended framework, SENS3 has the potential to be expanded with additional textures and participants. We anticipate that SENS3 will be valuable for advancing multisensory texture rendering, user experience development, and touch sensing in robotics.<br>
当前,人们对与技术开展自然交互的需求持续攀升,凸显了在数字环境中实现逼真触觉感知的重要性。要实现这一目标,高度依赖于覆盖全面的手指-表面交互数据库,而此类数据库仍有待进一步完善与发展。我们在此推出SENS3——网址为www.sens3.net——这是一个大规模的开放获取多感官数据库,收录了50种表面在两名参与者用指尖通过静态接触、按压、点击和滑动方式探索时采集到的数据。SENS3涵盖了此类交互过程中记录的高保真视觉、听觉与触觉信息,具体包括视频、音频、接触力、扭矩、位置、加速度、皮肤温度、热通量以及表面照片。此外,该数据库还收录了13名参与者在自由探索这些表面时的心理物理感知评分,涵盖粗糙-光滑、平整-凹凸、粘性-滑腻、温热-冰凉、规则-不规则、细腻-粗糙、坚硬-柔软以及湿润-干燥等维度。SENS3采用开放式架构设计,具备扩展更多材质纹理与参与者数据的潜力。我们预计,SENS3将对推动多感官纹理渲染、用户体验开发以及机器人触觉感知领域的发展具有重要价值。
提供机构:
4TU.ResearchData
创建时间:
2024-07-10
搜集汇总
数据集介绍

背景与挑战
背景概述
SENS3是一个开放存取的多感官数据库,记录了50种表面在手指交互过程中的高保真视觉、听觉和触觉数据,并包含13名参与者的心理物理感觉评分。该数据集旨在推动多感官纹理渲染、用户体验开发和机器人触觉传感的研究。
以上内容由遇见数据集搜集并总结生成



