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2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023

作者： Cannavò, Alberto Kapralos, Bill Seinfeld, Sofia Pratticò, Filippo Gabriele Zhang, Congyi Politecnico di Torino Turin Italy Game Development and Interactive Media Program and MaxSIMhealth Lab Ontario Tech University Oshawa Canada Image Processing and Multimedia Technology Center Universitat Politècnica de Catalunya-Barcelona Tech Terrassa Spain Politecnico di Torino Turin Italy Department of Computer Science The University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9798350348392

Today, Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) technologies are becoming fundamental across a wide variety of application domains. All these technologies fall under the Extended Reality (XR) spectrum. Areas in which XR technologies and, in particular, immersive experiences have been successfully introduced are expanding daily, from traditional areas, such as entertainment and video game production, to novel scenarios, such as industry, healthcare, smart cities, and autonomous vehicles, to mention a few. The spread of XR and VR is also driven by technological advancements that are making new ways of operating within virtual experiences easier, and sometimes even possible. In particular, the availability of new hardware and software tools make the use of '3D reconstructions', 'digital twins' and 'simulations' commonplace in many XR and VR applications. For example, the possibility to leverage networks with higher bandwidth than never before and lower latency makes it possible to transmit the amount of data needed for massive, real-time digital twins, whereas high-performance hardware enables the reconstruction of high-fidelity digital objects and environments, while lowering the time needed for high-demanding simulations. The aim of the 3D Reconstruction, Digital Twinning, and Simulation for Virtual Experiences (ReDigiTS) workshop is to bring together researchers, practitioners, educators, and students to share ideas and promote further work in this growing area of 3D reconstruction, digital twinning, and simulation in VR and related technologies. © 2023 IEEE.

关键词： Augmented reality

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Adaptive Neural Network Control for a Robotic Manipulator with Unknown Deadzone

Adaptive Neural Network Control for a Robotic Manipulator wi...

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第三十二届中国控制会议

作者： Shuzhi Sam Ge Wei He Shengtao Xiao Robotics Institute and School of Computer Science and Engineering University of Electronic Science and Technology of China Department of Electrical & Computer Engineering National University of Singapore Social Robotics Lab Interactive Digital Media InstituteNational University of Singapore Robotics Institute and School of Automation Engineering University of Electronic Science and Technology of China

ISBN: (纸本)9781479900305

In this paper,adaptive neural network control is designed for a robotic manipulator with unknown *** networks are used to compensate for the unknown deadzone effect faced by the manipulator's ***-feedback control is proposed first and high-gain observer is then designed to make the proposed control scheme more *** deadzone effect is approximated by a Radial Basis Function Neural Network(RBFNN) and the tracking error for the deadzone effect is bounded and *** unknown dynamics of the robotic manipulator is estimated with another *** for the estimated deadzone effect in the control law then leads to our proposed *** proposed control is then verified on a two-joint rigid manipulator via numerical simulations.

关键词： Neural network control Unknown deadzone Radial basis function neural network(RBFNN) Robotic manipulator.

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Adaptive demosaicking using multiple neural networks

Adaptive demosaicking using multiple neural networks

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2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, MLSP 2006

作者： Yangjing, Long Yizhen, Huang Department of Mathematics Shanghai Jiaotong University 800 Dongchuan Road Minhang District Shanghai 200240 China Department of Computer Science and Engineering Shanghai Jiaotong University 800 Dongchuan Road Minhang District Shanghai 200240 China Digital Media and Data Reconstruction Lab. Shanghai Jiaotong University Graphics Team of the Wireless Platform Engineering Cellular and Handheld Group Intel Asia-Pacific Research and Development Ltd.

ISBN: (纸本)1424406560

Demosaicking is one of the important tasks in the image-processing pipeline in digital cameras using a single electronic sensor overlaid with a Color Filter Array. We quantitatively shows that, demosaicking algorithms perform better in low-gradient flat areas than in high-gradient steep areas. Based on this, an adaptive scheme is proposed that uses more complex neural networks to tackle steep areas in larger sizes of neighborhoods. And interpolation is edge-directed with different networks for different chosen directions. Thus networks are specialized in learning and depicting non-linear spatial inter-pixel correlations at respective gradients and directions. Its performance surpasses Go's neural-network method greatly. Compared with 2 recent state-of-the-art methods, our method provides an excellent trade-off between computational expense and PSNR, and well preserves image edge information. As an extension, we compare the performance of these algorithms with and without Lukac's postprocessing. © 2006 IEEE.

关键词： Adaptive systems

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Super-resolution using neural networks based on the optimal recovery theory

Super-resolution using neural networks based on the optimal ...

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2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, MLSP 2006

作者： Huang, Yizhen Long, Yangjing Department of Computer Science and Engineering Shanghai Jiaotong University 800 Dongchuan Road Minhang District Shanghai 200240 China Department of Mathematics Shanghai Jiaotong University 800 Dongchuan Road Minhang District Shanghai 200240 China Graphics Team of the Wireless Platform Engineering Cellular and Handheld Group Intel Asia-Pacific Research and Development Ltd. Digital Media and Data Reconstruction Lab. Shanghai Jiaotong University

ISBN: (纸本)1424406560

An optimal recovery based neural-network Super Resolution algorithm is developed. The proposed method is computationally less expensive and outputs images with high subjective quality, compared with previous neural-network or optimal recovery algorithms. It is evaluated on classical SR test images with both generic and specialized training sets, and compared with other state-of-the-art methods. Results show that our algorithm is among the state-of-the-art, both in quality and efficiency. © 2006 IEEE.

关键词： Image quality

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Learning compliance control of robot manipulators in contact with the unknown environment

Learning compliance control of robot manipulators in contact...

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2010 IEEE International Conference on Automation science and Engineering, CASE 2010

作者： Li, Yanan Yang, Chenguang Ge, Shuzhi Sam Social Robotics Lab. NUS Graduate School for Integrative Sciences and Engineering National University of Singapore Singapore 119613 Singapore Department of Bioengineering Imperial College London London SW7 2AZ United Kingdom Department of Electrical and Computer Engineering Interactive Digital Media Institute National University of Singapore Singapore 117576 Singapore Institute of Intelligent Systems University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9781424454471

In this paper, a control mechanism is presented to improve the compliance performance of the robot manipulator when it is in contact with the unknown environment. This mechanism guarantees that the dynamics of the whole system follows a target impedance model so that the desired compliance performance is obtained. In particular, under the assumption that the dynamics is periodic, a learning law is developed to estimate the unknown dynamics parameters. Besides, the proposed systematic learning control does not require the accurate force measurement. Its performance and robustness are discussed in details by the rigorous analysis. At last, the validity of the proposed method is verified by simulation. © 2010 IEEE.

关键词： Modular robots

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Corsetto: A Kinesthetic Garment for Designing, Composing for, and Experiencing an Intersubjective Haptic Voice 23

Corsetto: A Kinesthetic Garment for Designing, Composing for...

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Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

作者： Ozgun Kilic Afsar Yoav Luft Kelsey Cotton Ekaterina R. Stepanova Claudia Núñez-Pacheco Rebecca Kleinberger Fehmi Ben Abdesslem Hiroshi Ishii Kristina Höök MIT Media Lab Massachusetts Institute of Technology United States Media Technology and Interaction Design KTH Royal Institute of Technology Sweden Division of Interaction Design at Department of Computer Science and Engineering Chalmers University of Technology Sweden Sweden School of Interactive Arts and Technology Simon Fraser University Canada College of Art Media & Design Northeastern University United States and MIT Media Lab Massachusetts Institute of Technology United States RISE SICS Computer Systems Sweden

ISBN: (纸本)9781450394215

We present a novel intercorporeal experience – an intersubjective haptic voice. Through an autobiographical design inquiry, based on singing techniques from the classical opera tradition, we created Corsetto, a kinesthetic garment for transferring somatic reminiscents of vocal experience from an expert singer to a listener. We then composed haptic gestures enacted in the Corsetto, emulating upper-body movements of the live singer performing a piece by Morton Feldman named Three Voices. The gestures in the Corsetto added a haptics-based ‘fourth voice’ to the immersive opera performance. Finally, we invited audiences who were asked to wear Corsetto during live performances. Afterwards they engaged in micro-phenomenological interviews. The analysis revealed how the Corsetto managed to bridge inner and outer bodily sensations, creating a feeling of a shared intercorporeal experience, dissolving boundaries between listener, singer and performance. We propose that ‘intersubjective haptics’ can be a generative medium not only for singing performances, but other possible intersubjective experiences.

关键词： voice micro-phenomenology haptics machine learning Robotic textiles shape changing interfaces somaesthetic interaction design

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A digital mobile choir: Joining two interfaces towards composing and performing collaborative mobile music 12th

A digital mobile choir: Joining two interfaces towards compo...

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12th International conference on New Interfaces for Musical Expression, NIME 2012

作者： D’alessandro, Nicolas Pon, Aura Wang, Johnty Eagle, David Sharlin, Ehud Fels, Sidney numediart – Institute for New Media Art Technology of the University of Mons MonsB-7000 Belgium Interactions Lab Dept. of Computer Science of the University of Calgary CalgaryT2N 1N4 Canada MAGIC – Media and Graphics Interdisciplinary Centre of the University of British Columbia VancouverV6T 1Z4 Canada Department of Music Faculty of Fine Arts of the University of Calgary CalgaryT2N 1N4 Canada

We present the integration of two musical interfaces into a new music-making system that seeks to capture the experience of a choir and bring it into the mobile space. This system relies on three pervasive technologies that each support a different part of the musical experience. First, the mobile device application for performing with an artificial voice, called ChoirMob. Then, a central composing and conducting application running on a local interactive display, called Vuzik. Finally, a network protocol to synchronize the two. ChoirMob musicians can perform music together at any location where they can connect to a Vuzik central conducting device displaying a composed piece of music. We explored this system by creating a chamber choir of ChoirMob performers, consisting of both experienced musicians and novices, that performed in rehearsals and live concert scenarios with music composed using the Vuzik interface. © 2012, Steering Committee of the International Conference on New Interfaces for Musical Expression. All rights reserved.

关键词： Music

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Welcome to ACM its 2014

ITS 2014 - Proceedings of the 2014 ACM International Confere...

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ITS 2014 - Proceedings of the 2014 ACM International Conference on interactive Tabletops and Surfaces 2014年 iii-iv页

作者： Dachselt, Raimund Graham, Nicholas Hornbæk, Kasper Nacenta, Miguel Interactive Media Lab Technische Universität Dresden United States School of Computing Queen's University Canada Department of Computer Science DIKU University of Copenhagen Denmark SACHI Research Group University of St Andrews United Kingdom

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Punctuated simplification of man-made objects

Punctuated simplification of man-made objects

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作者： Jang, Justin Wonka, Peter Ribarsky, William Shaw, Christopher D. Georgia Institute of Technology GVU Center College of Computing Atlanta GA 30332 United States Arizona State University PRISM Dept. of Computer Science and Engineering Tempe AZ 85287 United States UNC Charlotte CS Dept. Charlotte Visualization Center Charlotte NC 28223 United States Simon Fraser University Surrey School of Interactive Arts and Technology 14-660 Central City Tower 13450 102 Ave Surrey BC V3T 5X3 Canada Graphics Visualization and Usability Center Georgia Institute of Technology PRISM Lab. ASU Department of Information Technology UNC Charlotte Charlotte Visualization Center IEEE Visualization and Graphics Technical Committee School of Interactive Arts and Technology Simon Fraser University Surrey

We present a simplification algorithm for manifold polygonal meshes of plane-dominant models. Models of this type are likely to appear in man-made environments. While traditional simplification algorithms focus on generality and smooth meshes, the approach presented here considers a specific class of man-made models. By detecting and classifying edge loops on the mesh and providing a guided series of binary mesh partitions, our approach generates a series of simplified models, each of which better respects the semantics of these kinds of models than conventional approaches do. A guiding principle is to eliminate simplifications that do not make sense in constructed environments. This, coupled with the concept of "punctuated simplification", leads to an approach that is both efficient and delivers high visual quality. Comparative results are given.

关键词： Object oriented programming

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Deep learning - A first meta-survey of selected reviews across scientific disciplines, their commonalities, challenges and research impact

arXiv

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arXiv 2020年

作者： Egger, Jan Pepe, Antonio Gsaxner, Christina Jin, Yuan Li, Jianning Kern, Roman Institute of Computer Graphics and Vision Faculty of Computer Science and Biomedical Engineering Graz University of Technology Graz Austria Computer Algorithms for Medicine Laboratory Graz Austria Department of Oral and Maxillofacial Surgery Medical University of Graz Graz Austria University Medicine Essen Essen Germany Research Center for Connected Healthcare Big Data Zhejiang Lab Zhejiang Hangzhou China Research Unit Experimental Neurotraumatology Department of Neurosurgery Medical University of Graz Graz Austria Knowledge Discovery Know-Center Graz Austria Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria

Deep learning belongs to the field of artificial intelligence, where machines perform tasks that typically require some kind of human intelligence. Deep learning tries to achieve this by drawing inspiration from the learning of a human brain. Similar to the basic structure of a brain, which consists of (billions of) neurons and connections between them, a deep learning algorithm consists of an artificial neural network, which resembles the biological brain structure. Mimicking the learning process of humans with their senses, deep learning networks are fed with (sensory) data, like texts, images, videos or sounds. These networks outperform the state-of-the-art methods in different tasks and, because of this, the whole field saw an exponential growth during the last years. This growth resulted in way over 10,000 publications per year in the last years. For example, the search engine PubMed alone, which covers only a sub-set of all publications in the medical field, provides already over 11,000 results in Q3 2020 for the search term 'deep learning', and around 90% of these results are from the last three years. Consequently, a complete overview over the field of deep learning is already impossible to obtain and, in the near future, it will potentially become difficult to obtain an overview over a subfield. However, there are several review articles about deep learning, which are focused on specific scientific fields or applications, for example deep learning advances in computer vision or in specific tasks like object detection. With these surveys as a foundation, the aim of this contribution is to provide a first high-level, categorized meta-survey of selected reviews on deep learning across different scientific disciplines and outline the research impact that they already have during a short period of time. The categories (computer vision, language processing, medical informatics and additional works) have been chosen according to the underlying data sources (image,

关键词： Surveys

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