检索结果-内蒙古大学图书馆

23rd ieee International conference on Mobile Data Management (ieee MDM)

作者： Sun, Yunkai Nielsen, Nichlas Xie, Xike Pedersen, Torben Bach Simonsen, Ulf Lu, Hua Ainciburu, Maite Univ Sci & Technol China Beijing Peoples R China Aalborg Univ Aalborg Denmark Roskilde Univ Roskilde Denmark Polytech Montpellier Montpellier France

ISBN: (数字)9781665451765

ISBN: (纸本)9781665451765

The prevalence of mobile devices and positioning techniques has enabled so-called traffic-aware urban computing. In urban daily life, people's activities consist of indoor and outdoor parts whose transitions have important impacts on traffic behavior. For example, outdoor traffic events (e.g., jams) can be triggered by indoor events (e.g., the ending of exhibitions, tournaments, or working hours). In turn, indoor events (e.g., subway jams) can also be affected by outdoor events (e.g., snowy weather or other bad outdoor traffic conditions). For a wide range of applications like traffic monitoring and emergency response, it is thus interesting to develop techniques for analyzing data in an integrated indoor and outdoor space. Since real datasets of this kind are still scarce and small, a suitable data generator is needed for both functional and scalability testing. In this work, we present UrbanGen, which follows the constraints of road networks for the outdoor space and the constraints of topologies for the indoor space. The system provides the functionalities including: 1) integrating a model of indoor topologies with the state-of-art road networks;2) parameterizing the movement of objects in the integrated model;3) serializing and visualizing the generated trajectories.

关键词： trajectories in- and outdoor spaces moving objects visualization

来源：评论

学校读者我要写书评

暂无评论

Magnetometer-free Kalman filter for motor-based assessment of prodromal Parkinson's disease 44

Magnetometer-free Kalman filter for motor-based assessment o...

引用

44th Annual International conference of the ieee-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Guaitolini, M. Rovini, E. Galperti, G. Fiorini, L. Cavallo, F. Scuola Super Sant Anna BioRobot Inst I-56127 Pisa Italy Scuola Super Sant Anna Dept Excellence Robot & AI I-56127 Pisa Italy Univ Florence Dept Ind Engn Florence Italy

ISBN: (数字)9781728127828

ISBN: (纸本)9781728127828

Observing the kinematics of specific motor tasks, such as finger tapping (FT), provides an objective and consistent quantification of the severity of neurodegenerative diseases. However, the current clinical practice mostly relies on visual observations performed by the clinician. Thus, the assessment is subjective. In this paper, we propose a magnetometer-free Kalman filter (KF) to assess FT features using wearable, inertial sensors. The KF was used to assess features during two different FT tasks, namely forefinger tapping (FTAP) and thumb-forefinger tapping (THFF). The proposed KF was validated against a camera-based reference and compared with a strap-down integration-based method. Comparison between KF method and camera reference showed low discrepancies in terms of root mean square error (RMSE) for considered features: namely number of repetitions (RMSE < 0.7), tapping frequency (RMSE < 0.1 Hz), and amplitude (RMSE < 2.6 deg). An high correlation coefficient between amplitudes was also obtained. The proposed KF performed better than the strap-down integration method on both FT tasks, showing lower RMSE on every feature as well as a higher correlation coefficient.

关键词： visualization Magnetometers Tracking Magnetic separation Thumb Sensor fusion Kalman filters

来源：评论

学校读者我要写书评

暂无评论

OBJECTFOLDER 2.0: A Multisensory Object Dataset for Sim2Real Transfer

OBJECTFOLDER 2.0: A Multisensory Object Dataset for Sim2Real...

引用

ieee/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Gao, Ruohan Si, Zilin Chang, Yen-Yu Clarke, Samuel Bohg, Jeannette Li Fei-Fei Yuan, Wenzhen Wu, Jiajun Stanford Univ Stanford CA 94305 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

Objects play a crucial role in our everyday activities. Though multisensory object-centric learning has shown great potential lately, the modeling of objects in prior work is rather unrealistic. OBJECTFOLDER 1.0 is a recent dataset that introduces 100 virtualized objects with visual, acoustic, and tactile sensory data. However;the dataset is small in scale and the multisensory data is of limited quality, hampering generalization to real-world scenarios. We present OBJECTFOLDER 2.0, a large-scale, multisensory dataset of common household objects in the form of implicit neural representations that significantly enhances OBJECTFOLDER 1.0 in three aspects. First, our dataset is 10 times larger in the amount of objects and orders of magnitude faster in rendering time. Second, we significantly improve the multisensory rendering quality for all three modalities. Third, we show that models learned from virtual objects in our dataset successfully transfer to their real-world counterparts in three challenging tasks: object scale estimation, contact localization, and shape reconstruction. OBJECTFOLDER 2.0 offers a new path and testbed for multisensory learning in computer vision and robotics. The dataset is available at https: //***/rhgao/ObjectFolder.

关键词： Location awareness Computer vision visualization Shape Computational modeling Estimation Rendering (computer graphics)

来源：评论

学校读者我要写书评

暂无评论

Sub-word Level Lip Reading With Visual Attention

Sub-word Level Lip Reading With Visual Attention

引用

ieee/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Prajwal, K. R. Afouras, Triantafyllos Zisserman, Andrew Univ Oxford Visual Geometry Grp Oxford England

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

The goal of this paper is to learn strong lip reading models that can recognise speech in silent videos. Most prior works deal with the open-set visual speech recognition problem by adapting existing automatic speech recognition techniques on top of trivially pooled visual features. Instead, in this paper, we focus on the unique challenges encountered in lip reading and propose tailored solutions. To this end, we make the following contributions: (1) we propose an attention-based pooling mechanism to aggregate visual speech representations;(2) we use sub-word units for lip reading for the first time and show that this allows us to better model the ambiguities of the task;(3) we propose a model for Visual Speech Detection (VSD), trained on top of the lip reading network. Following the above, we obtain state-of-the-art results on the challenging LRS2 and LRS3 benchmarks when training on public datasets, and even surpass models trained on large-scale industrial datasets by using an order of magnitude less data. Our best model achieves 22.6% word error rate on the LRS2 dataset, a performance unprecedented for lip reading models, significantly reducing the performance gap between lip reading and automatic speech recognition. Moreover, on the AVA-ActiveSpeaker benchmark, our VSD model surpasses all visual-only baselines and even outperforms several recent audio-visual methods.

关键词： Voice activity detection Training visualization Lips Computational modeling Benchmark testing Data models

来源：评论

学校读者我要写书评

暂无评论

ARIA: Adversarially Robust Image Attribution for Content Provenance

ARIA: Adversarially Robust Image Attribution for Content Pro...

引用

ieee/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Andriushchenko, Maksym Li, Xiaoyang Rebecca Oxholm, Geoffrey Gittings, Thomas Bui, Tu Flammarion, Nicolas Collomosse, John EPFL Vaud Switzerland Adobe Res San Jose CA USA Univ Surrey Guildford GU2 5XH Surrey England

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Image attribution - matching an image back to a trusted source - is an emerging tool in the fight against online misinformation. Deep visual fingerprinting models have recently been explored for this purpose. However, they are not robust to tiny input perturbations known as adversarial examples. First we illustrate how to generate valid adversarial images that can easily cause incorrect image attribution. Then we describe an approach to prevent imperceptible adversarial attacks on deep visual fingerprinting models, via robust contrastive learning. The proposed training procedure leverages training on l(infinity)-bounded adversarial examples, it is conceptually simple and incurs only a small computational overhead. The resulting models are substantially more robust, are accurate even on unperturbed images, and perform well even over a database with millions of images. In particular, we achieve 91.6% standard and 85.1% adversarial recall under l(infinity)-bounded perturbations on manipulated images compared to 80.1% and 0.0% from prior work. We also show that robustness generalizes to other types of imperceptible perturbations unseen during training. Finally, we show how to train an adversarially robust image comparator model for detecting editorial changes in matched images. Project page: https://***/robust_image_attribution.

关键词： Training Location awareness Heating systems visualization Perturbation methods Computational modeling Fingerprint recognition

来源：评论

学校读者我要写书评

暂无评论

Development of an Ultra Low-Cost SSVEP-based BCI Device for Real-Time On-Device Decoding 44

Development of an Ultra Low-Cost SSVEP-based BCI Device for ...

引用

44th Annual International conference of the ieee-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Teversham, James Wong, Steven S. Hsieh, Bryan Rapeaux, Adrien Troiani, Francesca Savolainen, Oscar Zhang, Zheng Maslik, Michal Constandinou, Timothy G. Imperial Coll London Dept Elect & Elect Engn South Kensington Campus London SW7 2AZ England Imperial Coll London Ctr Bioinspired Technol South Kensington Campus London SW7 2AZ England Imperial Coll London Dept Life Sci South Kensington Campus London SW7 2AZ England Imperial Coll London UK Dementia Res Inst UKDRI Care Res & Technol CR&T London England Univ Surrey Guildford Surrey England

ISBN: (数字)9781728127828

ISBN: (纸本)9781728127828

This study details the development of a novel, approx. 20 pound electroencephalogram (EEG)-based brain-computer interface (BCI) intended to offer a financially and operationally accessible device that can be deployed on a mass scale to facilitate education and public engagement in the domain of EEG sensing and neurotechnologies. Real-time decoding of steady-state visual evoked potentials (SSVEPs) is achieved using variations of the widely-used canonical correlation analysis (CCA) algorithm: multi-set CCA and generalised CCA. All BCI functionality is executed on board an inexpensive ESP32 microcontroller. SSVEP decoding accuracy of 95.56 +/- 3.74% with an ITR of 102 bits/min was achieved with modest calibration.

关键词： visualization Microcontrollers Real-time systems Electroencephalography Decoding Steady-state Sensors

来源：评论

学校读者我要写书评

暂无评论

Visual Analysis of Spatio-temporal Phenomena with 1D Projections

引用

COMPUTER GRAPHICS FORUM 2021年第3期40卷 335-347页

作者： Franke, M. Martin, H. Koch, S. Kurzhals, K. Univ Stuttgart Stuttgart Germany Swiss Fed Inst Technol Zurich Switzerland Inst Adv Res Artificial Intelligence Vienna Austria

It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio-temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial context can be helpful for understanding details, but have proven to be less effective for overview and comparison tasks. We present an interactive approach for the exploration of spatio-temporal data, based on a set of neighborhood-preserving 1D projections which help identify patterns and support the comparison of numerous time steps and multivariate data. An important objective of the proposed approach is the visual description of local neighborhoods in the 1D projection to reveal patterns of similarity and propagation. As this locality cannot generally be guaranteed, we provide a selection of different projection techniques, as well as a hierarchical approach, to support the analysis of different data characteristics. In addition, we offer an interactive exploration technique to reorganize and improve the mapping locally to users' foci of interest. We demonstrate the usefulness of our approach with different real-world application scenarios and discuss the feedback we received from domain and visualization experts.

关键词： CCS Concepts • Human-centered computing → Visual analytics Geographic visualization information visualization visualization systems and tools

来源：评论

学校读者我要写书评

暂无评论

Decentralized Multi-robot Velocity Estimation for UAVs Enhancing Onboard Camera-based Velocity Measurements

Decentralized Multi-robot Velocity Estimation for UAVs Enhan...

引用

ieee/RSJ International conference on Intelligent Robots and Systems (IROS)

作者： Horyna, Jiri Kratky, Vit Ferrante, Eliseo Saska, Martin Czech Tech Univ Fac Elect Engn Multirobot Syst Grp Tech 2 Prague Czech Republic Technol Innovat Inst Autonomous Res Robot Ctr Abu Dhabi U Arab Emirates

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

Within the field of multi-robot systems, developing systems that rely only on onboard sensing without the use of external infrastructure (e.g. GNSS) has many potential applications. However, relying only on visual-based modalities for localization presents challenges in terms of accuracy and reliability. We introduce a decentralized multi-robot lateral velocity estimation method for Unmanned Aerial Vehicles (UAVs) to improve onboard measurements in case GNSS infrastructure is not available. This method relies on sharing the onboard measurements of neighbors, as well as the estimation of the relative motion of a focal UAV within the swarm, based on observation of coworking robots. The proposed velocity estimation method does not rely on centralized communication to achieve high reliability and scalability within the swarm system. The performance of the state estimation approach has been verified in simulations and real-world experiments. The results have shown that a swarm of UAVs using the proposed velocity estimator can stabilize individual robots when their primary onboard localization source is not reliable enough.

关键词： Location awareness Global navigation satellite system visualization Tracking Estimation Autonomous aerial vehicles Sensors

来源：评论

学校读者我要写书评

暂无评论

TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions

TransWeather: Transformer-based Restoration of Images Degrad...

引用

ieee/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Valanarasu, Jeya Maria Jose Yasarla, Rajeev Patel, Vishal M. Johns Hopkins Univ Baltimore MD 21218 USA

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

Removing adverse weather conditions like rain, fog, and snow from images is an important problem in many applications. Most methods proposed in the literature have been designed to deal with just removing one type of degradation. Recently, a CNN-based method using neural architecture search (All-in-One) was proposed to remove all the weather conditions at once. However;it has a large number of parameters as it uses multiple encoders to cater to each weather removal task and still has scope for improvement in its performance. In this work, we focus on developing an efficient solution for the all adverse weather removal problem. To this end, we propose TransWeather, a transformer-based end-to-end model with just a single encoder and a decoder that can restore an image degraded by any weather condition. Specifically, we utilize a novel transformer encoder using intra-patch transformer blocks to enhance attention inside the patches to effectively remove smaller weather degradations. We also introduce a transformer decoder with learnable weather type embeddings to adjust to the weather degradation at hand. TransWeather achieves significant improvements across multiple test datasets over both All-in-One network as well as methods fine-tuned for specific tasks. TransWeather is also validated on real world test images and found to be more effective than previous methods. Implementation code can be found in the supplementary document.

关键词： Degradation visualization Codes Machine vision Snow Transformers Image restoration

来源：评论

学校读者我要写书评

暂无评论

Visual Perception of Robot Appearance Attributes in the Peripheral Field of View Depends on Human Observer Eye-Movement Behaviors 39

Visual Perception of Robot Appearance Attributes in the Peri...

引用

ieee International conference on Robotics and Automation (ICRA)

作者： Kuehnlenz, Kolja Kuehnlenz, Barbara Coburg Univ Appl Sci & Art Robot Res Lab Dept Elect Engn & Comp Sci D-96450 Coburg Germany Coburg Univ Appl Sci & Arts Acad Ctr Sci & Humanities D-96450 Coburg Germany

ISBN: (纸本)9781728196817

This paper presents results from a study on the perception of robot attributes by human observers in their peripheral field of view depending on types of eye-movements of the latter. A between-subjects design is used, where a picture of a robot head is presented on a screen in the peripheral field of view of the participants with two conditions of eye-movements: static and pursuit. The two conditions are realized by a dot to be tracked by the participants, which is placed either in the center of the screen or moving linearly between left and right screen margins. As a subjective measure for appearance attributes, anthropomorphism is used using the multi-component Human-Robot Interaction Evaluation Scale (HRIES). Significant differences are revealed in the sociability and agency sub-scales of HRIES with respect to eye-movement behaviors. The results show, that humans perceive robot appearance attributes differently depending on whether or not pursuit eye-movements are conducted supporting the main hypothesis. Further, for pursuit movements, the scale center is rated for these sub-scales, which may indicate, that the particular robot characteristic is perceived less distinctively. No significant interactions are found for animacy and disturbance, which may be due to less applicability of these sub-scales to static images. The findings may have an impact on close interaction between humans and robots and potential anthropomorphism-related influences on task accomplishment to be considered in interaction design.

关键词： Heating systems visualization Head Sensitivity Observers Robot sensing systems Behavioral sciences

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：