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IEEE International Conference on Image Processing

作者： J.P. Lewis Iman Mostafavi Gina Sosinsky Maryanne E. Martone Ruth West Stanford University Computer Graphics Lab UC San Diego Computer Science and Engineering National Center for Microscopy and Imaging Research

Modern image processing techniques increasingly use prior models of the expected distribution of objects. Principal component eigen-models are often selected for shape prior modeling, but are limited in capturing only the second order moment statistics. On the other hand, kernel densities can in concept reproduce arbitrary statistics, but are problematic for high dimensional data such as shapes. An evident approach is to combine these methods, using PCA to reduce the problem dimensionality, followed by kernel density modeling of the PCA coefficients. In this paper we show that useful algorithmic and editing operations can be formulated in term of this simple approach. The operations are illustrated in the context of point distribution shape models. Particular points can be rapidly evaluated as being plausible or outliers, and a plausible shape can be completed given limited operator input in a manually guided procedure. This "PCA+KD" approach is conceptually simple, scalable (becoming increasingly accurate with additional training data), provides improved modeling power, and supports useful algorithmic queries.

关键词： Shape Kernel Principal component analysis Statistical distributions Tomography Image processing Training data Power system modeling Noise shaping computer graphics

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2-D passive millimeter wave imaging system for plasma diagnostics

2-D passive millimeter wave imaging system for plasma diagno...

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Asia-Pacific Microwave Conference, APMC 2007

作者： Shen, Zuowei Domier, C.W. Luhmann Jr., N.C. Ito, N. Mase, A. Donné, A.J.H. Park, H.K. Department of Electrical and Computer Engineering UC Davis United States Art Science and Technology Center for Cooperative Research Kyushu University Japan FOM-Institute for Plasma Physics Rijnhuizen Association EURATOM-FOM Nieuwegein Netherlands Princeton Plasma Physics Laboratory Princeton University United States

ISBN: (纸本)1424407494

Technology advances have made possible the visualization of electron temperature profiles and fluctuations inside the core of high temperature plasmas via a twodimensional passive millimeter wave imaging system. The electron cyclotron emission imaging (ECEI) system concept and configuration are briefly described. Advanced technologies such as frequency selective surfaces band-stop filter, planar Schottky diode mixer arrays, wide bandwidth IF electronics, and imaging optics are presented.

关键词： Notch filters

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Wide bandwidth mixer array development in millimeter wave imaging systems for plasma diagnostics

Wide bandwidth mixer array development in millimeter wave im...

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International Conference on Infrared and Millimeter Waves

作者： Zuowei Shen Naoki Ito Zhengang Xia Calvin. W. Domier Atsushi Mase N. C. Luhmann Department of Electrical and Computer Engineering UC Davis Davis CA USA Art Science and Technology Center for Cooperative Research Kyushu University Kasuga JAPAN

The development of imaging arrays on dielectric lens antennas for use in millimeter wave imaging systems is described. The 24-element 140-170 GHz and 22-element 110-140 GHz imaging mixer array are comprised of Schottky diodes and double dipole antenna arrays placed on an elliptical lens. This paper first describes the antenna development and then the characterization of the off-axis performance of the elliptical lens. The unequal spacing between antennas and channel number of the antenna arrays are determined based on the theoretically calculated off-axis far field patterns. A wide bandwidth balun used to reduce the mixer IF loss is also described.

关键词： Bandwidth Plasma diagnostics Dipole antennas Antenna arrays Lenses Millimeter wave technology Microwave imaging Plasma waves Impedance matching Schottky diodes

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D-band double dipole antenna for use in millimeter wave imaging systems

D-band double dipole antenna for use in millimeter wave imag...

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Antennas and Propagation Society International Symposium

作者： Z. Shen N. Ito E. Sakata C. W. Domier N. C. Luhmann{SuffixJr.} A. Mase Department of Electrical and Computer Engineering University of California Davis USA Art Science and Technology Center for Cooperative Research Kyushu University Japan Kyushu Hitachi Maxell Limited Japan Department of Electrical and Computer Engineering University of Canterbury Davis USA Department of Electrical and Computer Engineering UC Davis USA

ISBN: (纸本)9781424408771;1424408776

The design and experimental investigation of a D-Band coplanar stripline-fed double dipole antenna is presented. Double dipole antennas are designed for operation at 110-170 GHz as the imaging array elements for two millimeter wave imaging systems for plasma diagnostics. The antenna patterns are measured on high density polyethylene (HDPE) elliptical lenses. The wide bandwidth antenna has clean patterns with low side lobe levels and narrow beam width, and thus can provide good image resolution and low inter-channel crosstalk.

关键词： Dipole antennas Millimeter wave measurements High-resolution imaging Stripline Antenna arrays Plasma diagnostics Antenna measurements Density measurement Plasma measurements Polyethylene

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Contributors to the Lab on a Chip cell and tissue engineering in microsystems special issue

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Lab on a Chip 2007年第6期7卷 667-671页

作者： Bhatia, Sangeeta N. Chen, Christoper Bashir, Rashid Beebe, David J. Desai, Tejal Gottwald, Eric Khademhosseini, Ali Langer, Robert S. Piel, Matthieu Takayama, Shuichi Thorsen, Todd Tien, Joe Voldman, Joel Vunjak-Novakovic, Gordana Wu, Mingming Yu, Hanry Massachusetts Institute of Technology Harvard-MIT Division of Health Sciences and Technology Department of Electrical Engineering and Computer Science United States Laboratory for Multiscale Regenerative Technologies United States Department of Innovation University of Pennsylvania Department of Bioengineering United States Cell Biology and Physiology Program Cell Growth and Cancer Program Tissue Microfabrication Laboratory Department of Electrical and Computer Engineering and Biomedical Engineering Purdue University United States Department of Electronics University of Glasgow United Kingdom Department of Physiology and Bioengineering University of California San Francisco CA United States California Institute for Quantitative Biomedical Research UCSF/UC Berkeley Graduate Group in Bioengineering United States Laboratory of Therapeutic Micro and Nanotechnology Institute for Biological Interfaces Germany 3D-Cell Culture Techniques Group Institute for Biological Interfaces Germany Department of Medicine and Health Sciences and Technology Massachusetts Institute of Technology (MIT) United States Institut Curie UMR 144 IC/CNRS France Biomedical Engineering Department University of Michigan United States Department of Biomedical Engineering Macromolecular Science and Engineering Program United States Sibley School of Mechanical and Aerospace Engineering School of Chemical and Molecular Engineering Cornell University United States National University of Singapore Singapore Institute of Bioengineering and Nanotechnology A STAR Singapore

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Adaptive non-linear clustering in data streams 06

Adaptive non-linear clustering in data streams

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15th ACM Conference on Information and Knowledge Management, CIKM 2006

作者： Jain, Ankur Zhang, Zhihua Chang, Edward Y. Computer Science UC Santa Barbara CA 93106 Electrical and Computer Engineering UC Santa Barbara CA 93106

ISBN: (纸本)1595934332

Data stream clustering has emerged as a challenging and interesting problem over the past few years. Due to the evolving nature, and one-pass restriction imposed by the data stream model, traditional clustering algorithms are inapplicable for stream clustering. This problem becomes even more challenging when the data is high-dimensional and the clusters are not linearly separable in the input space. In this paper, we propose a nonlinear stream clustering algorithm that adapts to the stream's evolutionary changes. Using the kernel methods for dealing with the non-linearity of data separation, we propose a novel 2-tier stream clustering architecture. Tier-1 captures the temporal locality in the stream, by partitioning it into segments, using a kernel-based novelty detection approach. Tier-2 exploits this segment structure to continuously project the streaming data nonlinearly onto a low-dimensional space (LDS), before assigning them to a cluster. We demonstrate the effectiveness of our approach through extensive experimental evaluation on various real-world datasets. Copyright 2006 ACM.

关键词： Data mining

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Understanding the causes of packet delivery success and failure in dense wireless sensor networks 06

Understanding the causes of packet delivery success and fail...

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SenSys'06: 4th International Conference on Embedded Networked Sensor Systems

作者： Srinivasan, Kannan Dutta, Prabal Tavakoli, Arsalan Levis, Philip Department of Electrical Engineering Stanford University Computer Science Division UC Berkeley

ISBN: (纸本)1595933433

We present empirical measurements of the packet delivery performance of the Telos and MicaZ sensor platforms. At a high level, their behavior is similar to that of earlier platforms. They exhibit a reception "grey region," and temporal variations in packet loss. Looking more deeply, however, there are subtle differences, and looking deeper still, the patterns behind these complexities become clear. Environmental noise (802.11b) has high spatial correlation. Packet loss occurs when a receiver operating near its noise floor experiences a small decrease in received signal strength, rather than an increase in environmental noise. These variations cause the reception "grey region." Packet losses are highly correlated over short time periods, but are independent over longer periods. Based on these findings, current practices could be easily changed that would greatly improve efficiency and performance.

关键词： Wireless sensor networks

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computer aided assessment with human oversight

Computer aided assessment with human oversight

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ITiCSE06: 11th Annual SIGCSE Conference on Innovation and Technology in computer science Education

作者： Winters, Titus Payne, Tom Computer Science and Engineering Department UC Riverside Riverside CA 92521 United States

No abstract available

ISBN: (纸本)1595930558

No abstract available

关键词： computer aided assessment

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Identifying color in motion in video sensors

Identifying color in motion in video sensors

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2006 IEEE computer Society Conference on computer Vision and Pattern Recognition, CVPR 2006

作者： Wu, Gang Rahimi, Amir Goh, Kingshy Tsai, Tomy Jain, Ankur Wu, Yi Chang, Edward Y. Wang, Yuan-Fang Electrical and Computer Engineering UC Santa Barbara CA 93106 Computer Science UC Santa Barbara CA 93106 Proximex Inc. Cupertino CA 95014 Intel Inc. Santa Clara CA 95054

ISBN: (纸本)0769525970

Identifying or matching the surface color of a moving object in surveillance video is critical for achieving reliable object-tracking and searching. Traditional color models provide little help, since the surface of an object is usually not flat, the object's motion can alter the surface's orientation, and the lighting conditions can vary when the object moves. To tackle this research problem, we conduct extensive data mining on video clips collected under various lighting conditions and distances from several video-cameras. We observe how each of the eleven culture colors can drift in the color space when an object's surface is in motion. In the color space, we then learn the drift pattern of each culture color for classifying unseen surface colors. Finally, we devise a distance function taking color drift into consideration to perform color identification and matching. Empirical studies show our approach to be very promising: achieving over 95% color-prediction accuracy. © 2006 IEEE.

关键词： Image sensors

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Towards a mobile-robot following controller using behavioral cues

Towards a mobile-robot following controller using behavioral...

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2006 IEEE International Conference on Industrial Technology, ICIT

作者： Chueh, Michael Joshi, Sanjay Yeung, Yi Lin Au Lei, Kim-Pang University of California Davis 95616 United States Department of Computer Science IEEE Department of Mechanical and Aeronautical Engineering Computer Science Graduate Group Bainer Hall UC Davis Davis CA 95616-5294 United States

ISBN: (纸本)1424407265

This paper describes work towards a mobile-robot following controller which has the ability to incorporate a leader's behavioral cues into its controller formulation. The paper presents the mathematical formulation of the controller, and presents robot experimental studies used to investigate the controller. The controller continuously estimates the future predicted position of the leader (robot or human) as he/she/it moves, and then directs the follower robot to this position. A Kalman filter is employed for estimation that uses vision-based measurements of leader position, a dynamics model of the leader, and a behavioral-cue model of the leader. Singer's model is used to propagate the leader's state. A behavioral-cue model serves to create pseudo-measurements to further help the Kalman filter estimate the leader's future position. The controller is implemented on an ER Scorpion robot. Experiments are conducted using several different controllers. Results demonstrate that compared to other controllers, the proposed controller can more consistently follow the leader around sharp corners where line-of-sight is lost, as can happen often in indoor environments. However, in cases of more gradual movement where line-of-sight is not lost, a simpler vision-only controller has advantages.

关键词： Kalman filters

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