Proceedings of the 24th International Conference on Intelligent User Interfaces最新文献_第4页

PATI PATI

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302326

Yuxiang Gao, Chien-Ming Huang

{"title":"PATI","authors":"Yuxiang Gao, Chien-Ming Huang","doi":"10.1145/3301275.3302326","DOIUrl":"https://doi.org/10.1145/3301275.3302326","url":null,"abstract":"As robots begin to provide daily assistance to individuals in human environments, their end-users, who do not necessarily have substantial technical training or backgrounds in robotics or programming, will ultimately need to program and \"re-task\" their robots to perform a variety of custom tasks. In this work, we present PATI---a Projection-based Augmented Table-top Interface for robot programming---through which users are able to use simple, common gestures (e.g., pinch gestures) and tools (e.g., shape tools) to specify table-top manipulation tasks (e.g., pick-and-place) for a robot manipulator. PATI allows users to interact with the environment directly when providing task specifications; for example, users can utilize gestures and tools to annotate the environment with task-relevant information, such as specifying target landmarks and selecting objects of interest. We conducted a user study to compare PATI with a state-of-the-art, standard industrial method for end-user robot programming. Our results show that participants needed significantly less training time before they felt confident in using our system than they did for the industrial method. Moreover, participants were able to program a robot manipulator to complete a pick-and-place task significantly faster with PATI. This work indicates a new direction for end-user robot programming.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115181888","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: 29

Investigating the feasibility of finger identification on capacitive touchscreens using deep learning 研究利用深度学习技术在电容触摸屏上进行手指识别的可行性

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302295

Huy Viet Le, Sven Mayer, N. Henze

{"title":"Investigating the feasibility of finger identification on capacitive touchscreens using deep learning","authors":"Huy Viet Le, Sven Mayer, N. Henze","doi":"10.1145/3301275.3302295","DOIUrl":"https://doi.org/10.1145/3301275.3302295","url":null,"abstract":"Touchscreens enable intuitive mobile interaction. However, touch input is limited to 2D touch locations which makes it challenging to provide shortcuts and secondary actions similar to hardware keyboards and mice. Previous work presented a wide range of approaches to provide secondary actions by identifying which finger touched the display. While these approaches are based on external sensors which are inconvenient, we use capacitive images from mobile touchscreens to investigate the feasibility of finger identification. We collected a dataset of low-resolution fingerprints and trained convolutional neural networks that classify touches from eight combinations of fingers. We focused on combinations that involve the thumb and index finger as these are mainly used for interaction. As a result, we achieved an accuracy of over 92% for a position-invariant differentiation between left and right thumbs. We evaluated the model and two use cases that users find useful and intuitive. We publicly share our data set (CapFingerld) comprising 455,709 capacitive images of touches from each finger on a representative mutual capacitive touchscreen and our models to enable future work using and improving them.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127593553","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: 32

The role of user differences in customization: a case study in personalization for infovis-based content 用户差异在定制中的作用:基于信息可视化内容的个性化案例研究

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302283

Sébastien Lallé, C. Conati

{"title":"The role of user differences in customization: a case study in personalization for infovis-based content","authors":"Sébastien Lallé, C. Conati","doi":"10.1145/3301275.3302283","DOIUrl":"https://doi.org/10.1145/3301275.3302283","url":null,"abstract":"Although there is extensive evidence that personalization of interactive systems can improve the user's experience and satisfaction, it is also known that the two main approaches to deliver personalization, namely via customization or system-driven adaptation, have limitations. In particular, many users do not use customize mechanisms, while adaptation can be perceived as intrusive and opaque. In this paper, we explore an intermediary approach to personalization, namely delivering system-driven support to customization. To this end, we study a customization mechanism allowing to choose the type and amount of information displayed by means of information visualizations in a system for decision making, and examine the impact of user differences on the effectiveness of this mechanism. Our results show that, for the users who did use the customization mechanism, customization effectiveness was impacted by their levels of visualization literacy and locus of control. These results suggest that the customization mechanism could be improved by system-driven assistance to customize depending on the user's level of visualization literacy and locus of control.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116440854","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: 23

Inferencing underspecified natural language utterances in visual analysis 在视觉分析中推断未明确的自然语言话语

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302270

V. Setlur, Melanie Tory, Alex Djalali

引用次数: 50

Exemplar based experience transfer 基于范例的经验转移

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302300

Paridhi Maheshwari, Nitish Bansal, Surya Dwivedi, Rohan Kumar, Pranav Maneriker, Balaji Vasan Srinivasan

引用次数: 8

Supporting job mediator and job seeker through an actionable dashboard 通过可操作的仪表板支持工作中介和求职者

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302312

Sven Charleer, Francisco Gutiérrez, K. Verbert

引用次数: 5

Avoiding drill-down fallacies with VisPilot: assisted exploration of data subsets 使用VisPilot避免向下钻取谬误:辅助探索数据子集

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302307

D. Lee, Himel Dev, Huizi Hu, Hazem Elmeleegy, Aditya G. Parameswaran

{"title":"Avoiding drill-down fallacies with VisPilot: assisted exploration of data subsets","authors":"D. Lee, Himel Dev, Huizi Hu, Hazem Elmeleegy, Aditya G. Parameswaran","doi":"10.1145/3301275.3302307","DOIUrl":"https://doi.org/10.1145/3301275.3302307","url":null,"abstract":"As datasets continue to grow in size and complexity, exploring multi-dimensional datasets remain challenging for analysts. A common operation during this exploration is drill-down-understanding the behavior of data subsets by progressively adding filters. While widely used, in the absence of careful attention towards confounding factors, drill-downs could lead to inductive fallacies. Specifically, an analyst may end up being \"deceived\" into thinking that a deviation in trend is attributable to a local change, when in fact it is a more general phenomenon; we term this the drill-down fallacy. One way to avoid falling prey to drill-down fallacies is to exhaustively explore all potential drill-down paths, which quickly becomes infeasible on complex datasets with many attributes. We present VisPilot, an accelerated visual data exploration tool that guides analysts through the key insights in a dataset, while avoiding drill-down fallacies. Our user study results show that VisPilot helps analysts discover interesting visualizations, understand attribute importance, and predict unseen visualizations better than other multidimensional data analysis baselines.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134322910","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: 42

To explain or not to explain: the effects of personal characteristics when explaining music recommendations 解释或不解释:个人特征在解释音乐推荐时的影响

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302313

Martijn Millecamp, N. Htun, C. Conati, K. Verbert

{"title":"To explain or not to explain: the effects of personal characteristics when explaining music recommendations","authors":"Martijn Millecamp, N. Htun, C. Conati, K. Verbert","doi":"10.1145/3301275.3302313","DOIUrl":"https://doi.org/10.1145/3301275.3302313","url":null,"abstract":"Recommender systems have been increasingly used in online services that we consume daily, such as Facebook, Netflix, YouTube, and Spotify. However, these systems are often presented to users as a \"black box\", i.e. the rationale for providing individual recommendations remains unexplained to users. In recent years, various attempts have been made to address this black box issue by providing textual explanations or interactive visualisations that enable users to explore the provenance of recommendations. Among other things, results demonstrated benefits in terms of precision and user satisfaction. Previous research had also indicated that personal characteristics such as domain knowledge, trust propensity and persistence may also play an important role on such perceived benefits. Yet, to date, little is known about the effects of personal characteristics on explaining recommendations. To address this gap, we developed a music recommender system with explanations and conducted an online study using a within-subject design. We captured various personal characteristics of participants and administered both qualitative and quantitative evaluation methods. Results indicate that personal characteristics have significant influence on the interaction and perception of recommender systems, and that this influence changes by adding explanations. For people with a low need for cognition are the explained recommendations the most beneficial. For people with a high need for cognition, we observed that explanations could create a lack of confidence. Based on these results, we present some design implications for explaining recommendations.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131341195","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: 97

Discovering natural language commands in multimodal interfaces 在多模态界面中发现自然语言命令

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302292

Arjun Srinivasan, Mira Dontcheva, Eytan Adar, Seth Walker

引用次数: 30

MyoSign MyoSign

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302296

Qian Zhang, Dong Wang, Run Zhao, Yinggang Yu

{"title":"MyoSign","authors":"Qian Zhang, Dong Wang, Run Zhao, Yinggang Yu","doi":"10.1145/3301275.3302296","DOIUrl":"https://doi.org/10.1145/3301275.3302296","url":null,"abstract":"Automatic sign language recognition is an important milestone in facilitating the communication between the deaf community and hearing people. Existing approaches are either intrusive or susceptible to ambient environments and user diversity. Moreover, most of them perform only isolated word recognition, not sentence-level sequence translation. In this paper, we present MyoSign, a deep learning based system that enables end-to-end American Sign Language (ASL) recognition at both word and sentence levels. We leverage a lightweight wearable device which can provide inertial and electromyography signals to non-intrusively capture signs. First, we propose a multimodal Convolutional Neural Network (CNN) to abstract representations from inputs of different sensory modalities. Then, a bidirectional Long Short Term Memory (LSTM) is exploited to model temporal dependences. On the top of the networks, we employ Connectionist Temporal Classification (CTC) to get around temporal segments and achieve end-to-end continuous sign language recognition. We evaluate MyoSign on 70 commonly used ASL words and 100 ASL sentences from 15 volunteers. Our system achieves an average accuracy of 93.7% at word-level and 93.1% at sentence-level in user-independent settings. In addition, MyoSign can recognize sentences unseen in the training set with 92.4% accuracy. The encouraging results indicate that MyoSign can be a meaningful buildup in the advancement of sign language recognition.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115425672","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: 5