ViObject: Harness Passive Vibrations for Daily Object Recognition with Commodity Smartwatches

Wenqiang Chen, Shupei Lin, Zhencan Peng, Farshid Salemi Parizi, Seongkook Heo, Shwetak Patel, Wojciech Matusik, Wei Zhao, Jack Stankovic
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Abstract

Knowing the object grabbed by a hand can offer essential contextual information for interaction between the human and the physical world. This paper presents a novel system, ViObject, for passive object recognition that uses accelerometer and gyroscope sensor data from commodity smartwatches to identify untagged everyday objects. The system relies on the vibrations caused by grabbing objects and does not require additional hardware or human effort. ViObject's ability to recognize objects passively can have important implications for a wide range of applications, from smart home automation to healthcare and assistive technologies. In this paper, we present the design and implementation of ViObject, to address challenges such as motion interference, different object-touching positions, different grasp speeds/pressure, and model customization to new users and new objects. We evaluate the system's performance using a dataset of 20 objects from 20 participants and show that ViObject achieves an average accuracy of 86.4%. We also customize models for new users and new objects, achieving an average accuracy of 90.1%. Overall, ViObject demonstrates a novel technology concept of passive object recognition using commodity smartwatches and opens up new avenues for research and innovation in this area.
ViObject:利用商品智能手表的被动振动进行日常物体识别
了解手抓住的物体可以为人与物理世界的交互提供重要的上下文信息。本文介绍了一种用于被动物体识别的新型系统 ViObject,该系统利用来自商品智能手表的加速计和陀螺仪传感器数据来识别未标记的日常物体。该系统依赖于抓取物体时产生的振动,不需要额外的硬件或人力。ViObject 能够被动地识别物体,这对从智能家居自动化到医疗保健和辅助技术的广泛应用具有重要意义。在本文中,我们介绍了 ViObject 的设计和实现,以应对运动干扰、不同的物体触摸位置、不同的抓取速度/压力以及针对新用户和新物体的模型定制等挑战。我们使用来自 20 位参与者的 20 个对象的数据集对该系统的性能进行了评估,结果表明 ViObject 的平均准确率达到了 86.4%。我们还为新用户和新对象定制了模型,平均准确率达到 90.1%。总之,ViObject 展示了利用商品智能手表进行被动物体识别的新技术概念,并为该领域的研究和创新开辟了新途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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