Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops最新文献

Detecting Screen Presence with Activity-Oriented RGB Camera in Egocentric Videos. 在以自我为中心的视频中使用面向活动的RGB相机检测屏幕存在。

Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops Pub Date : 2022-03-01 Epub Date: 2022-05-06 DOI: 10.1109/percomworkshops53856.2022.9767433

Amit Adate, Soroush Shahi, Rawan Alharbi, Sougata Sen, Yang Gao, Aggelos K Katsaggelos, Nabil Alshurafa

{"title":"Detecting Screen Presence with Activity-Oriented RGB Camera in Egocentric Videos.","authors":"Amit Adate, Soroush Shahi, Rawan Alharbi, Sougata Sen, Yang Gao, Aggelos K Katsaggelos, Nabil Alshurafa","doi":"10.1109/percomworkshops53856.2022.9767433","DOIUrl":"https://doi.org/10.1109/percomworkshops53856.2022.9767433","url":null,"abstract":"Screen time is associated with several health risk behaviors including mindless eating, sedentary behavior, and decreased academic performance. Screen time behavior is traditionally assessed with self-report measures, which are known to be burdensome, inaccurate, and imprecise. Recent methods to automatically detect screen time are geared more towards detecting television screens from wearable cameras that record high-resolution video. Activity-oriented wearable cameras (i.e., cameras oriented towards the wearer with a fisheye lens) have recently been designed and shown to reduce privacy concerns, yet pose a greater challenge in capturing screens due to their orientation and fewer pixels on target. Methods that detect screens from low-power, low-resolution wearable camera video are needed given the increased adoption of such devices in longitudinal studies. We propose a method that leverages deep learning algorithms and lower-resolution images from an activity-oriented camera to detect screen presence from multiple types of screens with high variability of pixel on target (e.g., near and far TV, smartphones, laptops, and tablets). We test our system in a real-world study comprising 10 individuals, 80 hours of data, and 1.2 million low-resolution RGB frames. Our results outperform existing state-of-the-art video screen detection methods yielding an F1-score of 81%. This paper demonstrates the potential for detecting screen-watching behavior in longitudinal studies using activity-oriented cameras, paving the way for a nuanced understanding of screen time's relationship with health risk behaviors.","PeriodicalId":91950,"journal":{"name":"Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9704366/pdf/nihms-1835828.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40491666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Impacts of Image Obfuscation on Fine-grained Activity Recognition in Egocentric Video. 图像混淆对自我中心视频细粒度活动识别的影响。

Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops Pub Date : 2022-03-01 Epub Date: 2022-05-06 DOI: 10.1109/percomworkshops53856.2022.9767447

Soroush Shahi, Rawan Alharbi, Yang Gao, Sougata Sen, Aggelos K Katsaggelos, Josiah Hester, Nabil Alshurafa

{"title":"Impacts of Image Obfuscation on Fine-grained Activity Recognition in Egocentric Video.","authors":"Soroush Shahi, Rawan Alharbi, Yang Gao, Sougata Sen, Aggelos K Katsaggelos, Josiah Hester, Nabil Alshurafa","doi":"10.1109/percomworkshops53856.2022.9767447","DOIUrl":"https://doi.org/10.1109/percomworkshops53856.2022.9767447","url":null,"abstract":"Automated detection and validation of fine-grained human activities from egocentric vision has gained increased attention in recent years due to the rich information afforded by RGB images. However, it is not easy to discern how much rich information is necessary to detect the activity of interest reliably. Localization of hands and objects in the image has proven helpful to distinguishing between hand-related fine-grained activities. This paper describes the design of a hand-object-based mask obfuscation method (HOBM) and assesses its effect on automated recognition of fine-grained human activities. HOBM masks all pixels other than the hand and object in-hand, improving the protection of personal user information (PUI). We test a deep learning model trained with and without obfuscation using a public egocentric activity dataset with 86 class labels and achieve almost similar classification accuracies (2% decrease with obfuscation). Our findings show that it is possible to protect PUI at smaller image utility costs (loss of accuracy).","PeriodicalId":91950,"journal":{"name":"Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9704364/pdf/nihms-1835829.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40491665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

ActivityAware: An App for Real-Time Daily Activity Level Monitoring on the Amulet Wrist-Worn Device. ActivityAware:护身符腕带设备上的实时日常活动水平监测应用程序。

Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops Pub Date : 2017-03-01 Epub Date: 2017-05-04 DOI: 10.1109/PERCOMW.2017.7917601

George Boateng, John A Batsis, Ryan Halter, David Kotz

{"title":"ActivityAware: An App for Real-Time Daily Activity Level Monitoring on the Amulet Wrist-Worn Device.","authors":"George Boateng, John A Batsis, Ryan Halter, David Kotz","doi":"10.1109/PERCOMW.2017.7917601","DOIUrl":"https://doi.org/10.1109/PERCOMW.2017.7917601","url":null,"abstract":"Physical activity helps reduce the risk of cardiovascular disease, hypertension and obesity. The ability to monitor a person's daily activity level can inform self-management of physical activity and related interventions. For older adults with obesity, the importance of regular, physical activity is critical to reduce the risk of long-term disability. In this work, we present ActivityAware, an application on the Amulet wrist-worn device that measures daily activity levels (sedentary, moderate and vigorous) of individuals, continuously and in real-time. The app implements an activity-level detection model, continuously collects acceleration data on the Amulet, classifies the current activity level, updates the day's accumulated time spent at that activity level, logs the data for later analysis, and displays the results on the screen. We developed an activity-level detection model using a Support Vector Machine (SVM). We trained our classifiers using data from a user study, where subjects performed the following physical activities: sit, stand, lay down, walk and run. With 10-fold cross validation and leave-one-subject-out (LOSO) cross validation, we obtained preliminary results that suggest accuracies up to 98%, for n=14 subjects. Testing the ActivityAware app revealed a projected battery life of up to 4 weeks before needing to recharge. The results are promising, indicating that the app may be used for activity-level monitoring, and eventually for the development of interventions that could improve the health of individuals.","PeriodicalId":91950,"journal":{"name":"Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/PERCOMW.2017.7917601","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35035815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Measuring Changes in Gait and Vehicle Transfer Ability During Inpatient Rehabilitation with Wearable Inertial Sensors. 利用可穿戴惯性传感器测量住院康复期间步态和车辆转移能力的变化

Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops Pub Date : 2017-03-01 Epub Date: 2017-05-04 DOI: 10.1109/PERCOMW.2017.7917600

Vladimir Borisov, Gina Sprint, Diane J Cook, Douglas L Weeks

{"title":"Measuring Changes in Gait and Vehicle Transfer Ability During Inpatient Rehabilitation with Wearable Inertial Sensors.","authors":"Vladimir Borisov, Gina Sprint, Diane J Cook, Douglas L Weeks","doi":"10.1109/PERCOMW.2017.7917600","DOIUrl":"10.1109/PERCOMW.2017.7917600","url":null,"abstract":"Restoration of functional independence in gait and vehicle transfer ability is a common goal of inpatient rehabilitation. Currently, ambulation changes tend to be subjectively assessed. To investigate more precise objective assessment of progress in inpatient rehabilitation, we quantitatively assessed gait and transfer performances over the course of rehabilitation with wearable inertial sensors for 20 patients receiving inpatient rehabilitation services. Secondarily, we asked physical therapists to provide feedback about the clinical utility of metrics derived from the sensors. Participant performance was recorded on a sequence of ambulatory tasks that closely resemble everyday activities. We developed a custom software system to process sensor signals and compute metrics that characterize ambulation performance. We quantify changes in gait and transfer ability by performing a repeated measures comparison of the metrics one week apart. Metrics showing the greatest improvement are walking speed, stride regularity, acceleration root mean square, walking smoothness, shank peak angular velocity, and shank range of motion. Furthermore, feedback from physical therapists suggests that wearable sensor-derived metrics can potentially provide rehabilitation therapists with additional valuable information to aid in treatment decisions.","PeriodicalId":91950,"journal":{"name":"Proceedings of the ... IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom ... IEEE International Conference on Pervasive Computing and Communications. Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5497512/pdf/nihms-769687.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35155831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0