Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing最新文献_第4页

TextPursuits: using text for pursuits-based interaction and calibration on public displays textpursuit:在公共显示器上使用文本进行基于追踪的交互和校准

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971679

M. Khamis, Ozan Saltuk, Alina Hang, Katharina Stolz, A. Bulling, Florian Alt

引用次数: 76

Urban sensing based on human mobility 基于人类移动性的城市感知

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971735

Shenggong Ji, Yu Zheng, Tianrui Li

引用次数: 50

Engagement-aware computing: modelling user engagement from mobile contexts 参与感知计算:从移动环境建模用户参与

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971760

Akhil Mathur, N. Lane, F. Kawsar

引用次数: 47

Gait recognition using wifi signals 使用wifi信号进行步态识别

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971670

Wen Wang, A. Liu, Muhammad Shahzad

引用次数: 441

Predicting location semantics combining active and passive sensing with environment-independent classifier 结合主动和被动感知与环境无关分类器的位置语义预测

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971684

Masaya Tachikawa, T. Maekawa, Y. Matsushita

引用次数: 19

Toward practical factory activity recognition: unsupervised understanding of repetitive assembly work in a factory 走向实用的工厂活动识别:对工厂中重复性装配工作的无监督理解

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971721

T. Maekawa, Daisuke Nakai, Kazuya Ohara, Y. Namioka

引用次数: 55

The night is young: urban crowdsourcing of nightlife patterns 夜晚还很年轻:城市夜生活模式的众包

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971713

Darshan Santani, Joan-Isaac Biel, F. Labhart, J. Truong, Sara Landolt, E. Kuntsche, D. Gática-Pérez

{"title":"The night is young: urban crowdsourcing of nightlife patterns","authors":"Darshan Santani, Joan-Isaac Biel, F. Labhart, J. Truong, Sara Landolt, E. Kuntsche, D. Gática-Pérez","doi":"10.1145/2971648.2971713","DOIUrl":"https://doi.org/10.1145/2971648.2971713","url":null,"abstract":"We present a mobile crowdsourcing study to capture and examine the nightlife patterns of two youth populations in Switzerland. Our contributions are three fold. First, we developed a smartphone application to capture data on places, social context and nightlife activities, and to record mobile videos capturing the ambiance of places. Second, we conducted an \"in-the-wild\" study with more than 200 participants over a period of three months in two Swiss cities, resulting in a total of 1,394 unique place visits and 843 videos that spread across place categories (including personal homes and public parks), social and ambiance variables. Finally, we investigated the use of automatic ambiance features to estimate the loudness and brightness of places at scale, and found that while features are reliable with respect to video content, videos do not always reflect the place ambiance reported by people in-situ. We believe that the developed methodology provides an opportunity to understand the physical mobility, activities, and social context of youth as they experience different aspects of nightlife.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128298029","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: 40

Indoor localization via multi-modal sensing on smartphones 通过智能手机上的多模态传感进行室内定位

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971668

Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, K. Yi, Yunhao Liu

{"title":"Indoor localization via multi-modal sensing on smartphones","authors":"Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, K. Yi, Yunhao Liu","doi":"10.1145/2971648.2971668","DOIUrl":"https://doi.org/10.1145/2971648.2971668","url":null,"abstract":"Indoor localization is of great importance to a wide range of applications in shopping malls, office buildings and public places. The maturity of computer vision (CV) techniques and the ubiquity of smartphone cameras hold promise for offering sub-meter accuracy localization services. However, pure CV-based solutions usually involve hundreds of photos and pre-calibration to construct image database, a labor-intensive overhead for practical deployment. We present ClickLoc, an accurate, easy-to-deploy, sensor-enriched, image-based indoor localization system. With core techniques rooted in semantic information extraction and optimization-based sensor data fusion, ClickLoc is able to bootstrap with few images. Leveraging sensor-enriched photos, ClickLoc also enables user localization with a single photo of the surrounding place of interest (POI) with high accuracy and short delay. Incorporating multi-modal localization with Manifold Alignment and Trapezoid Representation, ClickLoc not only localizes efficiently, but also provides image-assisted navigation. Extensive experiments in various environments show that the 80-percentile error is within 0.26m for POIs on the floor plan, which sheds light on sub-meter level indoor localization.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123806097","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: 67

mSieve: differential behavioral privacy in time series of mobile sensor data mSieve:移动传感器数据时间序列中的差异行为隐私

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971753

Nazir Saleheen, Supriyo Chakraborty, Nasir Ali, Md. Mahbubur Rahman, Syed Monowar Hossain, Rummana Bari, E. Buder, M. Srivastava, Santosh Kumar

{"title":"mSieve: differential behavioral privacy in time series of mobile sensor data","authors":"Nazir Saleheen, Supriyo Chakraborty, Nasir Ali, Md. Mahbubur Rahman, Syed Monowar Hossain, Rummana Bari, E. Buder, M. Srivastava, Santosh Kumar","doi":"10.1145/2971648.2971753","DOIUrl":"https://doi.org/10.1145/2971648.2971753","url":null,"abstract":"Differential privacy concepts have been successfully used to protect anonymity of individuals in population-scale analysis. Sharing of mobile sensor data, especially physiological data, raise different privacy challenges, that of protecting private behaviors that can be revealed from time series of sensor data. Existing privacy mechanisms rely on noise addition and data perturbation. But the accuracy requirement on inferences drawn from physiological data, together with well-established limits within which these data values occur, render traditional privacy mechanisms inapplicable. In this work, we define a new behavioral privacy metric based on differential privacy and propose a novel data substitution mechanism to protect behavioral privacy. We evaluate the efficacy of our scheme using 660 hours of ECG, respiration, and activity data collected from 43 participants and demonstrate that it is possible to retain meaningful utility, in terms of inference accuracy (90%), while simultaneously preserving the privacy of sensitive behaviors.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121799107","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: 44

A data hiding approach for sensitive smartphone data 一种敏感智能手机数据的数据隐藏方法

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971686

Chu Luo, Angelos Fylakis, Juha Partala, Simon Klakegg, Jorge Gonçalves, K. Liang, T. Seppänen, V. Kostakos

引用次数: 16