The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition
The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition
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DOI：
10.1016/j.patrec.2012.12.014
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发表时间：
2013-11-01
影响因子：
5.1
通讯作者：
Roggen, Daniel
中科院分区：
文献类型：
--
作者：
Chavarriaga, Ricardo;Sagha, Hesam;Roggen, Daniel
人们越来越关注使用环境和可穿戴传感器进行人类活动识别，这是由几个应用领域和更广泛的传感技术所促进的。这引发了人们对开发利用多模态传感器设置的强大机器学习技术的越来越多的关注。然而，与其他应用程序不同，该领域没有既定的基准问题。事实上，方法通常在非常特定的实验设置中获得的自定义数据集上进行测试。此外，不同群体之间很少分享数据。我们的目标是通过引入在传感器丰富的环境中记录的多功能人类活动数据集来解决这个问题。该数据库是关于活动确认的公开挑战的基础。我们在这里报告了这一挑战的结果，以及使用不同分类技术的基线性能。我们希望这个基准数据库将激励其他研究人员复制和超越所提出的结果，从而有助于进一步推进最先进的活动识别方法。(C)2012爱思唯尔有限公司版权所有。
There is a growing interest on using ambient and wearable sensors for human activity recognition, fostered by several application domains and wider availability of sensing technologies. This has triggered increasing attention on the development of robust machine learning techniques that exploits multimodal sensor setups. However, unlike other applications, there are no established benchmarking problems for this field. As a matter of fact, methods are usually tested on custom datasets acquired in very specific experimental setups. Furthermore, data is seldom shared between different groups. Our goal is to address this issue by introducing a versatile human activity dataset recorded in a sensor-rich environment. This database was the basis of an open challenge on activity recognition. We report here the outcome of this challenge, as well as baseline performance using different classification techniques. We expect this benchmarking database will motivate other researchers to replicate and outperform the presented results, thus contributing to further advances in the state-of-the-art of activity recognition methods. (C) 2012 Elsevier B.V. All rights reserved.