2012 16th International Symposium on Wearable Computers最新文献

Toe Input Using a Mobile Projector and Kinect Sensor 脚趾输入使用移动投影仪和Kinect传感器

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.11

Daiki Matsuda, K. Uemura, Nobuchika Sakata, S. Nishida

引用次数: 15

Socio-Technical Network Analysis from Wearable Interactions 来自可穿戴交互的社会技术网络分析

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.19

K. Farrahi, R. Emonet, A. Ferscha

{"title":"Socio-Technical Network Analysis from Wearable Interactions","authors":"K. Farrahi, R. Emonet, A. Ferscha","doi":"10.1109/ISWC.2012.19","DOIUrl":"https://doi.org/10.1109/ISWC.2012.19","url":null,"abstract":"Wearable sensing platforms like modern smart phones have proven to be effective means in the complexity and computational social sciences. This paper draws from explicit (phone calls, SMS messaging) and implicit (proximity sensing based on Bluetooth radio signals) interaction patterns collected via smart phones and reality mining techniques to explain the dynamics of personal interactions and relationships. We consider three real human to human interaction networks, namely physical proximity, phone communication and instant messaging. We analyze a real undergraduate community's social circles and consider various topologies, such as the interaction patterns of users with the entire community, and the interaction patterns of users within their own community. We fit distributions of various interactions, for example, showing that the distribution of users that have been in physical proximity but have never communicated by phone fits a gaussian. Finally, we consider five types of relationships, for example friendships, to see whether significant differences exist in their interaction patterns. We find statistically significant differences in the physical proximity patterns of people who are mutual friends and people who are non-mutual (or asymmetric) friends, though this difference does not exist between mutual friends and never friends, nor does it exist in their phone communication patterns. Our findings impact a wide range of data-driven applications in socio-technical systems by providing an overview of community interaction patterns which can be used for applications such as epidemiology, or in understanding the diffusion of opinions and relationships.","PeriodicalId":190627,"journal":{"name":"2012 16th International Symposium on Wearable Computers","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129626105","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: 12

Kinect=IMU? Learning MIMO Signal Mappings to Automatically Translate Activity Recognition Systems across Sensor Modalities Kinect = IMU ?学习MIMO信号映射自动转换跨传感器模态的活动识别系统

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.17

O. Baños, Alberto Calatroni, M. Damas, H. Pomares, I. Rojas, Hesam Sagha, J. Millán, G. Tröster, Ricardo Chavarriaga, D. Roggen

{"title":"Kinect=IMU? Learning MIMO Signal Mappings to Automatically Translate Activity Recognition Systems across Sensor Modalities","authors":"O. Baños, Alberto Calatroni, M. Damas, H. Pomares, I. Rojas, Hesam Sagha, J. Millán, G. Tröster, Ricardo Chavarriaga, D. Roggen","doi":"10.1109/ISWC.2012.17","DOIUrl":"https://doi.org/10.1109/ISWC.2012.17","url":null,"abstract":"We propose a method to automatically translate a preexisting activity recognition system, devised for a source sensor domain S, so that it can operate on a newly discovered target sensor domain T, possibly of different modality. First, we use MIMO system identification techniques to obtain a function that maps the signals of S to T. This mapping is then used to translate the recognition system across the sensor domains. We demonstrate the approach in a 5-class gesture recognition problem translating between a vision-based skeleton tracking system (Kinect), and inertial measurement units (IMUs). An adequate mapping can be learned in as few as a single gesture (3 seconds) in this scenario. The accuracy after Kinect → IMU or IMU → Kinect translation is 4% below the baseline for the same limb. Translating across modalities and also to an adjacent limb yields an accuracy 8% below baseline. We discuss the sources of errors and means for improvement. The approach is independent of the sensor modalities. It supports multimodal activity recognition and more flexible real-world activity recognition system deployments.","PeriodicalId":190627,"journal":{"name":"2012 16th International Symposium on Wearable Computers","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130689859","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

Have We Achieved the Ultimate Wearable Computer? 我们实现了终极可穿戴电脑吗?

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.26

B. Thomas

引用次数: 17

Introducing a New Benchmarked Dataset for Activity Monitoring 为活动监控引入一个新的基准数据集

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.13

Attila Reiss, D. Stricker

引用次数: 884

Textile Interfaces: Embroidered Jog-Wheel, Beaded Tilt Sensor, Twisted Pair Ribbon, and Sound Sequins 纺织接口:刺绣慢跑轮，串珠倾斜传感器，双绞线带，和声音亮片

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.29

C. Zeagler, Scott M. Gilliland, Halley P. Profita, Thad Starner

引用次数: 39

Tongue Mounted Interface for Digitally Actuating the Sense of Taste 安装在舌头上的界面，用于数字驱动味觉

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.16

Nimesha Ranasinghe, R. Nakatsu, Hideaki Nii, G. Ponnampalam

{"title":"Tongue Mounted Interface for Digitally Actuating the Sense of Taste","authors":"Nimesha Ranasinghe, R. Nakatsu, Hideaki Nii, G. Ponnampalam","doi":"10.1109/ISWC.2012.16","DOIUrl":"https://doi.org/10.1109/ISWC.2012.16","url":null,"abstract":"Most of the systems for generating taste sensations are based on blending different chemicals appropriately, and there are less proven approaches to stimulate the sense of taste digitally. In this paper, a method to digitally stimulate the sense of taste is introduced and demonstrated based on electrical and thermal stimulation on human tongue. Thus, two digital control systems are presented to control taste sensations and their intensities effectively on the tongue. The effects of most persuading factors such as current, frequency, and temperature have been accounted to noninvasively stimulate the tongue. The initial experimental results indicate that sour (strong), bitter (mild), and salty(mild) are the main sensations, which can be evoked while there are evidences of sweet sensation too. Based on the results of the Tongue Mounted Digital Taste Interface, we have then developed another system which named as the Digital Sour Lollipop to effectively control the sour taste digitally. Initial experimental results of this system show the controllability of sour taste up to three levels of intensities using the electrical stimulation on human tongue.","PeriodicalId":190627,"journal":{"name":"2012 16th International Symposium on Wearable Computers","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114538231","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: 58

Airwriting: Hands-Free Mobile Text Input by Spotting and Continuous Recognition of 3d-Space Handwriting with Inertial Sensors 空中书写:用惯性传感器定位和连续识别3d空间手写的免提移动文本输入

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.21

C. Amma, Marcus Georgi, Tanja Schultz

{"title":"Airwriting: Hands-Free Mobile Text Input by Spotting and Continuous Recognition of 3d-Space Handwriting with Inertial Sensors","authors":"C. Amma, Marcus Georgi, Tanja Schultz","doi":"10.1109/ISWC.2012.21","DOIUrl":"https://doi.org/10.1109/ISWC.2012.21","url":null,"abstract":"We present an input method which enables complex hands-free interaction through 3d handwriting recognition. Users can write text in the air as if they were using an imaginary blackboard. Motion sensing is done wirelessly by accelerometers and gyroscopes which are attached to the back of the hand. We propose a two-stage approach for spotting and recognition of handwriting gestures. The spotting stage uses a Support Vector Machine to identify data segments which contain handwriting. The recognition stage uses Hidden Markov Models (HMM) to generate the text representation from the motion sensor data. Individual characters are modeled by HMMs and concatenated to word models. Our system can continuously recognize arbitrary sentences, based on a freely definable vocabulary with over 8000 words. A statistical language model is used to enhance recognition performance and restrict the search space. We report the results from a nine-user experiment on sentence recognition for person dependent and person independent setups on 3d-space handwriting data. For the person independent setup, a word error rate of 11% is achieved, for the person dependent setup 3% are achieved. We evaluate the spotting algorithm in a second experiment on a realistic dataset including everyday activities and achieve a sample based recall of 99% and a precision of 25%. We show that additional filtering in the recognition stage can detect up to 99% of the false positive segments.","PeriodicalId":190627,"journal":{"name":"2012 16th International Symposium on Wearable Computers","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122742890","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: 108

GazeCloud: A Thumbnail Extraction Method Using Gaze Log Data for Video Life-Log GazeCloud:一种基于注视日志数据的视频生命日志缩略图提取方法

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.32

Yoshio Ishiguro, J. Rekimoto

引用次数: 11

Urban Vibrations: Sensitivities in the Field with a Broad Demographic 城市振动:广泛人口领域的敏感性

2012 16th International Symposium on Wearable Computers Pub Date : 2012-06-18 DOI: 10.1109/ISWC.2012.10

A. Morrison, Lars Knudsen, H. J. Andersen

引用次数: 13