Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction最新文献_第2页

Deep Neural Network based Human Activity Recognition for the Order Picking Process 基于深度神经网络的拣货过程人类活动识别

Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction Pub Date : 2017-09-21 DOI: 10.1145/3134230.3134231

René Grzeszick, Jan Marius Lenk, Fernando Moya Rueda, G. Fink, S. Feldhorst, M. T. Hompel

{"title":"Deep Neural Network based Human Activity Recognition for the Order Picking Process","authors":"René Grzeszick, Jan Marius Lenk, Fernando Moya Rueda, G. Fink, S. Feldhorst, M. T. Hompel","doi":"10.1145/3134230.3134231","DOIUrl":"https://doi.org/10.1145/3134230.3134231","url":null,"abstract":"Although the fourth industrial revolution is already in pro-gress and advances have been made in automating factories, completely automated facilities are still far in the future. Human work is still an important factor in many factories and warehouses, especially in the field of logistics. Manual processes are, therefore, often subject to optimization efforts. In order to aid these optimization efforts, methods like human activity recognition (HAR) became of increasing interest in industrial settings. In this work a novel deep neural network architecture for HAR is introduced. A convolutional neural network (CNN), which employs temporal convolutions, is applied to the sequential data of multiple intertial measurement units (IMUs). The network is designed to separately handle different sensor values and IMUs, joining the information step-by-step within the architecture. An evaluation is performed using data from the order picking process recorded in two different warehouses. The influence of different design choices in the network architecture, as well as pre- and post-processing, will be evaluated. Crucial steps for learning a good classification network for the task of HAR in a complex industrial setting will be shown. Ultimately, it can be shown that traditional approaches based on statistical features as well as recent CNN architectures are outperformed.","PeriodicalId":209424,"journal":{"name":"Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114115083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 65

Where are my colleagues?: Tracking and Counting Multiple Persons using Lifted Marginal Filtering 我的同事呢?:使用提升边缘滤波对多人进行跟踪和计数

Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction Pub Date : 2017-09-21 DOI: 10.1145/3134230.3134237

S. Lüdtke, Max Schröder, Frank Krüger, T. Kirste

引用次数: 1

Experiences from a Wearable-Mobile Acquisition System for Ambulatory Assessment of Diet and Activity 可穿戴-移动采集系统对饮食和活动动态评估的经验

Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction Pub Date : 2017-09-21 DOI: 10.1145/3134230.3134239

Kristof Van Laerhoven, Mario Wenzel, A. Geelen, Christopher Hübel, M. Wolters, A. Hebestreit, L. Andersen, P. Veer, T. Kubiak

{"title":"Experiences from a Wearable-Mobile Acquisition System for Ambulatory Assessment of Diet and Activity","authors":"Kristof Van Laerhoven, Mario Wenzel, A. Geelen, Christopher Hübel, M. Wolters, A. Hebestreit, L. Andersen, P. Veer, T. Kubiak","doi":"10.1145/3134230.3134239","DOIUrl":"https://doi.org/10.1145/3134230.3134239","url":null,"abstract":"Public health trends are currently monitored and diagnosed based on large studies that often rely on pen-and-paper data methods that tend to require a large collection campaign. With the pervasiveness of smart-phones and -watches throughout the general population, we argue in this paper that such devices and their built-in sensors can be used to capture such data more accurately with less of an effort. We present a system that targets a pan-European and harmonised architecture, using smartphones and wrist-worn activity loggers to enable the collection of data to estimate sedentary behavior and physical activity, plus the consumption of sugar-sweetened beverages. We report on a unified pilot study across three countries and four cities (with different languages, locale formats, and data security and privacy laws) in which 83 volunteers were asked to log beverages consumption along with a series of surveys and longitudinal accelerometer data. Our system is evaluated in terms of compliance, obtained data, and first analyses.","PeriodicalId":209424,"journal":{"name":"Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127216047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Low-level Event Detection System for Minimally-Invasive Surgery Training 微创手术培训的低层次事件检测系统

Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction Pub Date : 2017-09-21 DOI: 10.1145/3134230.3134241

David Nieves, C. Ferri, J. Hernández-Orallo, Carlos Monserrat Aranda

引用次数: 0

Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction 第四届基于传感器的活动识别与交互国际研讨会论文集

Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction Pub Date : 1900-01-01 DOI: 10.1145/3134230

引用次数: 2