第五届中国科技大学《计算机图形学》暑期课程
USTC Summer
School 2016 (001M0601)
Advances in Computer Graphics
(计算机图形学前沿进展)
图形与几何计算实验室 (Graphics&Geometric
Computing Laboratory)
中国科学技术大学 (University
of Science and Technology of China)
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Announcements |
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2016年7月17日:中科大的选课的本科生的课程考核要求(点击进入),deadline:2016年8月29日。
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2016年6月28日:已通过系统向所有选课学员发送了注意事项(点击查看),请注意查看信箱。
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2016年6月28日:课程地点在中国科技大学东区的理化大楼,靠近科大东区南门(太湖路)附近(点击查看)。
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2016年6月28日:参加暑期课程的学员食宿自理。中国科技大学东校区周边酒店信息下载(供参考)。由于科大暑期活动很多,周边住宿会非常紧张。请外地学员及早自行预订住宿。
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2016年6月15日:注册人数已满,不再接受注册。
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2016年6月13日:注册人数即将满额,注册系统将在6月15日关闭。
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2016年6月06日:欢迎参加暑期课程的老师和同学也注册参加GDC 2016学术会议,在6月15日之前将享受优惠注册费,点击此处注册GDC
2016。
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2016年5月20日:课程开始注册。点击注册(注册之前请务必仔细查阅“课程注册说明文档”)。
注册名额有限。名额满后,即不再开放注册。
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2016年5月16日:参加暑期课程的学员食宿自理。中国科技大学东校区周边酒店信息下载(供参考)。由于科大暑期活动很多,周边住宿会非常紧张。请外地学员及早自行预订住宿。
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2016年5月16日:课程地点在中国科技大学东区的理化大楼,靠近科大东区南门(太湖路)附近,点击查看地图位置。
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2016年5月15日:第九届全国几何设计与计算学术会议(GDC
2016)是计算机图形学和几何建模、设计与计算方面的全国盛会,会议内容丰富,有众多的大会论文研究成果报告。特邀报告者包括University
of North Carolina at Chapel Hill的Dinesh Manocha教授,新加坡南洋理工的Jianmin
Zheng教授,中国科学院软件研究所的孙家昶教授和商飞北研中心仿真实验室的吴斌博士。多个小型专题研讨会,围绕当前本领域多个热点专题,邀请多名优秀学者针对专题发展现状和发展趋势展开深入讨论,包括快速建模、点云处理、3D打印、等几何分析。另外,大会还有Siggraph项目的经验panel,将邀请在Siggraph项目具有丰富经验的年轻教师与大家分享如何做研究的经验、体会、和技巧等。该暑期课程同时也作为GDC
2016会议的会前课程。可以单独注册参加暑期课程(免费),也可以同时注册参加GDC
2016大会(付费)!点击此处注册GDC
2016。
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2016年5月1日:注册系统将在5月中旬开放。名额有限,敬请关注。
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2016年2月18日:今年的暑期课程时间定为2016年7月11日至7月15日共5天。
课程在 第九届全国几何设计与计算学术会议(GDC
2016)之前举办,也同时作为GDC 2016的会前课程。授课计划初步确定,今年的课程将继续完全免费。
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课程介绍: |
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《计算机图形学前沿进展》(课程编号:001M06)为中国科技大学暑期学期的课程。课程由数学科学学院中科大图形与几何计算实验室(GCL)的刘利刚老师及国内外学者共同授课。本年度课程的主题为“3D几何感知与建模、
虚拟现实、机器人与人机交互”。若对计算机图形学中的几何处理不太熟悉的同学,可提前看一下
刘利刚老师开设的本科生课程《计算机图形学》(2013,2014,2015,
2016)和研究生课程《数字几何处理》的主页(其中有较完善的课程课件提供下载
)。
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该课程为中国科学技术大学全校性公共选修课程,面向应用数学、计算机科学、信息科学等相关专业的学生,欢迎数学学院、少年班学院、信息学院、计算机学院等学院的本科生高年级学生和研究生来选课
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若本校的本科生需要该课程的学分,需要在校教务系统中进行选课。
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该课程以介绍计算机图形学领域的最新的研究成果及进展为主,同时兼顾本科生也会介绍该领域的一些基本问题和研究方向,只要有《线性代数》、《微积分》、《解析几何》、《微分几何》等课程知识的学生都可以听懂。
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本次课程的内容涵盖几何建模、网格化技术、形状的感知分析、结构分析及功能性分析、点云处理、深度相机、细分造型技术、3D打印、虚拟现实
、机器人等内容,内容丰富和前沿,是了解计算机图形学前沿和未来方向的非常难得的机会。
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上课时间:2016年7月11日至7月15日
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上课地点:中国科学技术大学东区理化大楼西三报告厅
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学分:2
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课程安排: |
时间 |
授课老师 |
课程题目 |
7月11日
星期一 |
08:30-08:40 |
刘利刚 |
课程介绍 |
08:40-10:10 |
鲍虎军 |
混合现实技术-挑战、进展与展望
(1) |
10:25-11:30 |
鲍虎军 |
混合现实技术-挑战、进展与展望
(2) |
14:30-16:00 |
Xianfeng Gu (顾险峰) |
Discrete Surface Ricci Flow & Optimal Transportation |
16:15-17:45 |
李世鹏 |
Virtualize Everything: a Path to the Convergence of Cloud,
Mobile and IoT Computing |
7月12日
星期二 |
08:30-10:00 |
刘利刚 |
面向3D打印的几何设计与优化 |
10:15-11:45 |
Philip Chi-Wing Fu (傅志榮) |
Computational Interlocking for 3D Fabrication |
14:30-16:00 |
黄劲 |
弹性模拟中的线性化与降维 |
16:15-17:45 |
于雷 |
数字建造手段与计算图形学的逆向生成关系 |
7月13日
星期三 |
08:30-10:00 |
刘世霞 |
复杂文本数据可视分析:
人与数据的有机融合 |
10:15-11:45 |
Oliver Deussen |
Modeling and
Reconstruction of Complex Botanical Plants |
14:30-16:00 |
张方略 |
结构敏感的图像与视频智能编辑 |
16:15-17:45 |
傅孝明 |
无翻转和低形变的映射计算 |
7月14日
星期四 |
08:30-10:00 |
王涌天 |
增强现实头戴显示设备研究进展 |
10:15-11:45 |
田丰 |
笔式和多通道人机交互 |
14:30-16:00 |
王党校 |
力触觉人机交互——让虚拟世界真实可触 |
16:15-17:45 |
刘利刚 |
稀疏表达及其在几何处理中的应用 |
7月15日
星期五 |
08:30-10:00 |
Jianmin Zheng (郑建民) |
T-spline Theory and Applications |
10:15-11:45 |
Jia Pan (潘佳) |
Deep Visuomotor Control for Robots |
14:30-16:00 |
Dinesh Manocha |
Robot Motion Planning (1) |
16:15-17:45 |
Dinesh Manocha |
Robot Motion Planning (2) |
17:45-18:00 |
刘利刚 |
课程总结 |
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授课教师介绍: |
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Dinesh
Manocha, University of North Carolina at Chapel Hill, USA
http://www.cs.unc.edu/~dm
Dinesh Manocha is currently Phi Delta Theta/Matthew Mason
Distinguished Professor of Computer Science at the University of
North Carolina at Chapel Hill. He received his B.Tech degree in
Computer Science and Engineering from the Indian Institute of
Technology, Delhi in 1987; Ph.D. in Computer Science at the
University of California at Berkeley in 1992. He has coauthored more
than 420 papers in the leading conferences and journals on computer
graphics, robotics, and scientific computing. Manocha has received
many prestigious awards and 14 best paper awards at leading
conferences. He is a Fellow of ACM, AAAS, and IEEE and received
Distinguished Alumni Award from Indian Institute of Technology,
Delhi.
He has served on the editorial board of 10 leading journals and
program committees of 100+ conferences in computer graphics,
robotics, high performance computing, geometric computing, and
symbolic computation. He has been the program chair and general
chair of more than 13 conferences/workshops in these areas. He also
served as Director-at-large of ACM SIGGRAPH from 2011-2014.
Manocha has supervised 65+ M.S. and Ph.D. students over the last 23
years at UNC Chapel Hill. His research group has developed many
well-known software packages for collision detection, triangulation,
GPU-based algorithms, solid modeling and solving algebraic systems.
These packages have been downloaded by more than 150K users
worldwide and licensed to more than 55 industrial organizations, and
also widely used by robotics, CAD/CAM, and simulation communities.
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Oliver
Deussen, University of Konstanz, Germany
https://www.informatik.uni-konstanz.de/en/deussen/staff/oliver-deussen
Prof. Deussen graduated at Karlsruhe Institute of Technology
and is professor at University of Konstanz (Germany) and visiting
professor at SIAT Shenzhen (Chinese Academy of Science). In 2014 he
was awarded within the 1000 talents plan. He is Vice-President of
Eurographics Association and served as Editor in Chief of Computer
Graphics Forum from 2012-2016. His areas of interest are modeling
and rendering of complex biological systems, non-photorealistic
rendering as well as Information Visualization. He also contributed
papers to geometry processing, sampling methods, and image-based
modelling.
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Xianfeng
Gu
(顾险峰), State University of New York at Stony Brook, USA
http://www3.cs.stonybrook.edu/~gu
Xianfeng Gu got his bachelor degree from Tsinghua university
and PhD from Harvard university, supervised by the internationally
renowned differential geometer, Prof. Shing-Tung Yau. Dr. Gu and
Prof. Yau made fundamental contributions to an emerging
interdisciplinary field: Computational Conformal Geometry. Dr. Gu
won Morningside Gold Medal in Applied mathematics in 2013.
Currently, Dr. Gu is a tenured professor in Computer Science
department and Applied Mathematics department in the State
University of New York at Stony Brook.
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Jianmin
Zheng
(郑建民), Nanyang
Technological University, Singapore
http://www.ntu.edu.sg/home/asjmzheng
Jianmin Zheng is currently a tenured associate professor in
the School of Computer Science and Engineering at Nanyang
Technological University (NTU), Singapore. He received his BS and
PhD from Zhejiang University, China in 1986 and 1992, respectively.
Prior to joining NTU in 2003, he was a post-doc and a research staff
at Brigham Young University, and a professor in mathematics at
Zhejiang University. His research activities over the past years
covered computer aided geometric design, computer graphics, computer
aided design and manufacturing, visualization, simulation, virtual
reality, and interactive digital media. He was the conference
co-chair of Geometric Modeling and Processing 2014 and has served on
program committees of many international conferences. Dr Zheng is an
associate editor of The Visual Computer.
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Philip
Chi-Wing Fu (傅志榮), The Chinese University of Hong Kong
http://www.cse.cuhk.edu.hk/~cwfu
Chi-Wing Fu recently joined the Chinese University of Hong
Kong as an associate professor in January this year. Before that, he
was an associate professor in Nanyang Technological University,
Singapore. He obtained his PhD in Computer Science from Indiana
University Bloomington, USA. He is currently serving as the program
co-chair of SIGGRAPH ASIA 2016 technical brief and poster, and has
served in various technical program committees, including SIGGRAPH
ASIA technical brief, emerging technology, IEEE visualization, and
ACM CHI Work-in-Progress, as well as an associate editor of Computer
Graphics Forum. His research interests include computer graphics,
visualization, and human-computer interaction.
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Jia Pan
(潘佳),
The City University of Hong Kong
http://www.cityu.edu.hk/mbe/jiapan
Jia Pan is an assistant professor in the Department of
Mechanical and Biomedical Engineering, the City University of Hong
Kong. His research area is intelligent grasping and manipulation,
including motion planning, deformable object manipulation, learning
from demonstration, reinforcement learning and planning with
uncertainty.
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王党校,北京航空航天大学
http://haptic.buaa.edu.cn/chinese_team_teacherWang.htm
王党校,北京航空航天大学虚拟现实技术与系统国家重点实验室副教授,博士生导师,IEEE 触觉技术委员会(IEEE Technical
Committee on Haptics, TCH) 执行委员会主席,IEEE Transaction on Haptics编委(Associate
Editor)。中国计算机学会人机交互专业组常委。IEEE高级会员,中国计算机学会高级会员,中国机械工程学会高级会员。主要研究领域为力触觉人机交互、虚拟现实、机器人学。在IEEE
Transaction on Haptics、IEEE Transaction on Visualization and
Computer Graphics、IEEE Transactions on Instrumentation and
Measurement等刊物发表论文十余篇,在触觉领域顶级会议IEEE World Haptics
Conference、机器人领域知名会议IEEE ICRA和IEEE IROS等发表会议论文十余篇。2008年入选北京市科技新星,2013年获教育部技术发明一等奖(第三完成人),2011年在机器人和自动化领域顶级国际会议IEEE
ICRA获最佳论文提名奖。
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张方略,清华大学
http://cg.cs.tsinghua.edu.cn/people/~fanglue
张方略,清华大学博士后,2009年本科毕业于浙江大学数字媒体技术专业,2015年1月在清华大学计算机系获得博士学位。自2009年起,张方略一直从事图像与视频的理解分析与智能编辑方法的相关研究,在图像和视频的结构化表示与分析、图像与视频合成、基于感知的可视媒体分析与编辑方面都取得了一定的成果,相关论文均发表在计算机图形学领域的重要国际期刊和会议上,包括ACM
SIGGRAPH/SIGGRAPH Asia,ACM TOG, IEEE TVCG, IEEE
TIP等。2015年获博士后科学基金一等资助。
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刘利刚,中国科学技术大学
http://staff.ustc.edu.cn/~lgliu
刘利刚,中国科学技术大学教授,博士生导师,中国科学院“百人计划”,中国科学院特聘研究员。于2001年在浙江大学获得应用数学博士学位;2001年至2004年期间在微软亚洲研究院工作;2004年至2011年期间在浙江大学数学系工作。2009年至2011年期间,在美国哈佛大学进行学术访问研究。研究兴趣包括计算机图形学,3D几何建模与处理,3D打印等。已在计算机图形学顶级(TOP)期刊ACM
Transactions on
Graphics上发表论文十余篇。主持国家自然科学基金项目3项,2012年获得国家自然科学“优秀青年基金”项目。获得国家发明专利2项,计算机软件著作权15项。获得“微软青年教授”奖(2006)、陆增镛CAD&CG高科技奖一等奖(2010)、国家自然科学奖二等奖(2013)、中科大校友基金会青年教师事业奖(2014)等奖项。国际会议GMP
2017大会共同主席,SPM 2014, SGP 2015, CVM 2016的论文共同主席。学术期刊CGF, CAGD, IEEE
CG&A及《软件学报》编委。
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课程简介: |
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Title:
Robot Motion Planning Lecturer: Dinesh Manocha, University of
North Carolina at Chapel Hill, USA
Abstract: Motion is ubiquitous in both the real world
and synthetic environments. Representations of motion are central to
all computational disciplines that deal with modeling dynamical or
kinematic systems in the biological, physical or virtual world. For
example, interaction with objects in the virtual environment, design
and assembly of electronic appliances, animation of articulated
figures, manipulation of nano-structures, modeling of tissues and
muscles, etc. Recently, motion planning techniques are also used in
computer games and virtual worlds, as well as simulating the
behaviors of large number of human-like agents or crowds. In this
short course, we give an overview of techniques used to
automatically compute the motion and discuss various applications.
The set of topics include:
• Introduction to Motion Planning
• Configuration Spaces
• Sampling-Based Motion Planning Algorithms
• Fast Collision Checking
• Optimization Based Motion Planning Algorithms
• Applications to robotics, CAD and games.
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Title:
Modeling and reconstruction of complex botanical plants Lecturer:
Oliver Deussen, University of Konstanz, Germany Abstract:
Virtual plant models are needed in film and computer games, in
simulation, city and landscape planning, in forestry and many other
areas. We start with an introduction to fractal objects and then
discuss modeling approaches such as L-Systems and specializes
production algorithms, then data-based modeling and reconstruction
will be discussed.
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Title:
Discrete Surface Ricci Flow & Optimal Transportation Lecturer:
Xianfeng Gu (顾险峰), State University of New York at Stony Brook, USA Abstract:
This talk introduces two fundamental theoretic tools in geometric
processing, surface Ricci flow and Optimal transportation.
Surface mapping will introduce distortions, which can be classified
to angle distortion and area distortion. Ricci flow can produce
angle-preserving mappings, optimal mass transportation can induce
area-preserving mappings.
Surface Ricci flow deforms the surface Riemannian metric
proportional to the current curvature, such that the curvature
evolves according to a diffusion and reaction process, and
eventually the curvature converges to a constant. We formulate the
discrete surface Ricci flow as a variational problem, and use
Newton's method for the convex optimization. Furthermore, we prove
the existence and the uniqueness of the solution to the discrete
surface Ricci flow, which implies the classical surface
uniformization theorem. The methods can design Riemannian metrics
from prescribed curvatures.
Optimal mass transportation produces a homeomorphism which maps one
probability measure to the other in the most economical way. Optimal
transportation has intrinsic relation to the Minkowski problem in
convex geometry, and can be reduced to solve Monge-Ampere equation.
We give a variational approach to solve the Monge-Ampere equation,
which leads to a novel proof of Alexandrov theorem. The method can
be applied for computing Wasserstin distance between probability
measures.
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Title:
T-spline theory and applications Lecturer: Jianmin Zheng (郑建民), Nanyang
Technological University, Singapore
Abstract: This lecture will review T-splines, a
free-form surface technology introduced in 2003 as generalization of
NURBS. T-splines support non-tensor-product structure and have the
local refinement property. These features endow T-splines with
unique advantages over NURBS in geometry-based applications such as
CAD and CAE. It has been shown that T-splines can solve many
limitations inherent in existing NURBS based modeling. T-spline
technology was acquired by Autodesk in December 2011 and has been
incorporated into Autodesk's products such as Fusion 360. T-splines
also find applications in the area of iso-geometric analysis.
The lecture will be organized from basic spline geometry to T-spline
theory, typical applications and recent research. Students will
learn basic knowledge and some open research problems of the
subject.
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Title:
Computational Interlocking for 3D Fabrication Lecturer: Philip
Chi-Wing Fu (傅志榮), The Chinese University of Hong Kong
Abstract: Constructing a 3D object assembly is an
important topic of great interest in computer graphics research,
particularly in the areas of 3D printing, mechanical design, and
furniture modeling. The research problem involves the construction
of 3D component parts, the construction of joints for connecting the
component parts, as well as many other issues such as stability and
aesthetics. To create the component connections in making 3D
assembly, we first propose to employ the concept of mechanical
interlocking found in the well-known puzzle model known as the Burr
puzzle; the interesting property of this model is that in a finished
assembly, all the component parts are immobilized by the geometry,
except for a special key. Hence, we can tighten the connections
among the component parts in the assembly. Starting from this puzzle
model, we generalize the interlocking concept, and formulate various
novel computational methods for constructing mechanical interlocking
in different 3D fabrication forms, including our preliminary work in
the recursive interlocking puzzle models, later the
local-interlocking group concept for computing the joints in
furniture parts, and more recently the corner-based interlocking
mechanism for interlocking 2D laser-cut parts into a 3D polyhedral
object.
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Title:
Deep Visuomotor Control for Robots Lecturer: Jia Pan (潘佳), The City
University of Hong Kong
Abstract: To achieve high-speed, agile robot
movements with on-board sensing and computation only, we are working
on a fast reactive perception-action control loop. The control loop
directly runs on streaming first-person-perspective depth maps and
other fast retrievable data such as raw images, vehicle state
estimates, or even optical flows. We are using a policy that
directly maps from those inputs, as well as lower-frequency
structural, semantic, and goal information, to motor commands. These
models will train themselves autonomously using self-teaching
methods based on deep networks. Some results on using this framework
for multi-agent navigation will be shown.
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Title:
Virtualize Everything: a Path to the Convergence of Cloud, Mobile
and IoT Computing Lecturer: 李世鹏,科通芯城集团及硬蛋科技,首席技术官
Abstract: With the rapid development of Cloud
Computing, Mobile Computing and IoT Computing, there is an
increasing need for an efficient and effective way to enable the
collaborations between cloud, mobile devices and IoT devices to
bring new and compelling user experiences. In this lecture, the
speaker tries to point out a new path to realize the efficient
device collaboration. By effectively virtualize every possible user
interface that the user could possibly interact with and exposing
these virtualized UIs as a service, any devices could connect to
these services and leverage the computing resources, applications,
services, and natural UIs exposed by the virtualized UI and
aggregate them to achieve even more powerful capabilities, more apps
and services, more compelling experiences, more natural UIs on any
single computing devices. Furthermore, the UI data can be readily
extended to sensors data and control data commonly present in IoT
devices. Thus it makes the collaboration between IoT devices and
other devices becomes readily achievable.
The speaker using Titanium technology in the development as an
example to illustrate the points. Titanium technology is a
technology that most efficiently virtualizes and compresses both the
input and output data streams (bi-directional) of a computing device
and exposes them as a service that can be accessed through any data
networks by any other computing devices. At its core, Titanium
technology virtualizes and compresses the bi-directional input and
output data streams most efficiently in a rate-distortion sense
while minimizing computational cost involved so that they can be
virtualized without introducing performance degradation to local
applications and easily transported in real-time between different
computing devices through existing wired or wireless data networks.
Titanium Technology also offers object-level virtualization so that
objects within input and output data streams can be virtualized
independently and can be further combined into new virtualized input
and output data streams for other computing devices as needed. It
aggregates the computing, input and output resources available on
all computing devices in a network together and makes them all
available to any computing devices in the network. It also
virtualizes any contents, apps and services available on one
computing device without any modifications and makes them accessible
from any other computing devices. At a higher level, UI
virtualization also provide a third dimension of variables to
optimize computing experience in device and cloud collaboration
besides storage and computation, especially with object-based UI
virtualization.
The speaker will further point out that natural user interfaces for
effortless service discovery, device connection, and digital object
manipulation, etc., are crucial for the success of device
collaboration and new user experience. The speaker proposes some
possible solutions for this natural user interface among devices.
The whole device collaboration can be viewed an operating system for
the so-call Device Space. While traditionally on any single device,
we know the exact location of digital objects, in the device space,
we actually have to deal with the physical location of each device
besides the available digital information. This new operating system
for the device space has not been well studied yet. There are many
challenging yet exciting opportunity in this new area.
http://dsp.acm.org/view_lecturer.cfm?lecturer_id=5303
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历年暑期课程
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