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Exploring the use of proper orthogonal decomposition for enhancing blood flow images via computational fluid dynamics

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11th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2008

作者： McGregor, Robert Szczerba, Dominik Von Siebenthal, Martin Muralidhar, Krishnamurthy Székely, Gábor Computer Vision Laboratory Department of Electrical Engineering ETH Zürich 8092 Switzerland Department of Mechanical Engineering Indian Institute of Technology Kanpur Kanpur UP 208 016 India

ISBN: (纸本)3540859896

Obtaining high quality patient-specific flow velocity information is not an easy task. Available clinical data are usually poorly resolved and contain a significant amount of noise. We propose a novel approach to integrate computational fluid dynamics with measurement data to overcome this difficulty. By performing a proper orthogonal decomposition of simulated blood flow patterns for a given vascular location with various anatomical configurations it is possible to obtain a basis model for flow reconstruction. This is used to interpolate imaging data intelligently without having to perform a full flow simulation for each individual patient. This work focuses on assessing the feasibility of such a method. © 2008 Springer Berlin Heidelberg.

关键词： Computational fluid dynamics

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Moving object removal in video sequence and background restoration using kalman filter

Moving object removal in video sequence and background resto...

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International Symposium on Telecommunications, IST

作者： Saeed Kamel Hossein Ebrahimnezhad Afshin Ebrahimi Computer Vision Research Laboratory Electrical Engineering Department Sahand University of Technology Tabriz Iran

Object removal in image and video sequences has attracted many researchers in video processing. In this paper, a novel method is proposed to separate moving objects from background based on combination of Kalman filtering and background subtraction. Also, a video completion algorithm is proposed to remove the extracted objects. This algorithm uses the temporal information of frames to complete the holes appeared after object removal. The holes associated to the fixed objects in background model are removed and filled by image completion algorithm based on exemplar texture synthesis. Experimental results demonstrate the privilege performance of the proposed method in object removing and background restoration of real captured video sequences.

关键词： Kalman filters Pixel Motion segmentation computer vision Image color analysis Image restoration Filtering

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Building detection from aerial images using invariant color features and shadow information

Building detection from aerial images using invariant color ...

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International International Symposium on computer and Information Sciences (ISCIS)

作者： Beril Sirmacek Cem Unsalan Computer Vision Research Laboratory Department of Electrical and Electronics Engineering Yeditepe University Istanbul Turkey

Robust detection of buildings is an important part of the automated aerial image interpretation problem. Automatic detection of buildings enables creation of maps, detecting changes, and monitoring urbanization. Due to the complexity and uncontrolled appearance of the scene, an intelligent fusion of different methods gives better results. In this study, we present a novel approach for building detection using multiple cues. We benefit from segmentation of aerial images using invariant color features. Besides, we use the edge and shadow information for building detection. We also determine the shape of the building by a novel method.

关键词： Image edge detection Buildings Image segmentation Shape Data mining computer vision Gray-scale Testing Lighting Laboratories

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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Automated Facial Feature Detection from Portrait and Range Images

Automated Facial Feature Detection from Portrait and Range I...

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IEEE Southwest Symposium on Image Analysis and Interpretation

作者： Sina Jahanbin Alan C. Bovik Hyohoon Choi Department of Electrical and Computer Engineering University of Texas Austin USA Computer Vision Research Laboratory Sealed Air Corporation San Jose USA

ISBN: (纸本)9781424422968;1424422965

We propose a novel technique to detect feature points from portrait and range representations of the face. In this technique, the appearance of each feature point is encoded using a set of Gabor wavelet responses extracted at multiple orientations and spatial frequencies. A vector of Gabor coefficients, called a jet, is computed at each pixel in the search window on a fiducial and compared with a set of jets, called a bunch, collected from a set of training data on the same type of fiducial. The desired feature point is located at the pixel whose jet is the most similar to the training bunch. This is the first time that Gabor wavelet responses were used to detect facial landmarks from range images. This method was tested on 1146 pairs of range and portrait images and high detection accuracies are achieved using a small number of training images. It is shown that co-localization using Gabor jets on range and portrait images resulted in better accuracy than using any single image modality. The obtained accuracies are competitive to that of other techniques in the literature.

关键词： Facial features Face detection computer vision Face recognition Shape Nose Active appearance model Data mining Robustness Detection algorithms

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Distributed Data Association and Filtering for Multiple Target Tracking

Distributed Data Association and Filtering for Multiple Targ...

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26th IEEE Conference on computer vision and Pattern Recognition (CVPR 2008), vol.6

作者： Ting Yu Ying Wu Nils O. Krahnstoever Peter H. Tu GE Global Research Visualization and Computer Vision Laboratory Niskayuna NY USA Department of Electrical Engineering and Computer Sciences Northwestern University Evanston IL USA

This paper presents a novel distributed framework for multi-target tracking with an efficient data association computation. A decentralized representation of trackers' motion and association variables is adopted. Considering the interleaved nature of data association and tracker filtering, the multi-target tracking is formulated as a missing data problem, and the solution is found by the proposed variational EM algorithm. We analytically show that 1) the posteriori distributions of trackers' motions (the real interests in terms of tracking applications) can be effectively computed in the E-step of the EM iterations, and 2) the solution of trackers' association variables can be pursued under a derived graph-based discrete optimization formulation, thus efficiently estimated in the M-step by the recently emerging graph optimization algorithms. The proposed approach is very general such that sophisticated data association priori and likelihood function can be easily incorporated. This general framework is tested with both simulation data and real world surveillance video. The reported qualitative and quantitative studies verify the effectiveness and low computational cost of the algorithm.

关键词： Target tracking Distributed computing Filtering algorithms Algorithm design and analysis Motion analysis Motion estimation Testing Computational modeling Surveillance Computational efficiency

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Automated facial feature detection and face recognition using Gabor features on range and portrait images

Automated facial feature detection and face recognition usin...

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IEEE International Conference on Image Processing

作者： Sina Jahanbin Hyohoon Choi Rana Jahanbin Alan C. Bovik Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Computer Vision Research Laboratory Sealed Air Corporation San Jose CA USA Department of Biomedical Engineering University of Texas Austin Austin TX USA

In this paper, we present a novel identity verification system based on Gabor features extracted from range (3D) representations of faces. Multiple landmarks (fiducials) on a face are automatically detected using these Gabor features. Once the landmarks are identified, the Gabor features on all fiducials of a face are concatenated to form a feature vector for that particular face. Linear discriminant analysis (LDA) is used to reduce the dimensionality of the feature vector while maximizing the discrimination power. These novel features were tested on 1196 range images. The same features were also extracted from portrait images, and the accuracies of both modalities were compared. A superior verification accuracy was obtained using the range data, and a highly competitive accuracy to that of other techniques in the literature was also obtained for the portrait data.

关键词： Facial features Face detection Face recognition Biometrics Fingerprint recognition Iris Feature extraction Vectors Linear discriminant analysis Testing

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Effect of field of view on the Levitation Illusion

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Journal of Vestibular research 2008年第5-6期17卷 271 - 277页

作者： H.L. Jenkin J.E. Zacher M.R. Jenkin C.M. Oman L.R. Harris Department of Psychology York University Toronto CanadaCentre for Vision Research York University Toronto Canada Centre for Vision Research York University Toronto Canada Centre for Vision Research York University Toronto CanadaDepartment of Computer Science and Engineering York University Toronto Canada Man Vehicle Laboratory Massachusetts Institute of Technology USA

Supine subjects inside a furnished room in which both they and the room are pitched 90° backwards may experience themselves and the room as upright relative to gravity. This effect is known as the levitation illusion because observers report that their arms feel weightless when extended, and objects hanging in the room seem to "levitate". This illusion is an extreme example of a visually induced illusion of static tilt. Visually induced tilt illusions are commonly experienced in wide-screen movie theatres, flight simulators, and immersive virtual reality systems. For technical reasons an observer's field of view is often constrained in these environments. No studies have documented the effect of field-of-view (FOV) restriction on the incidence of the levitation illusion. Preliminary findings suggest that when concurrently manipulating the FOV and observer position within an environment, the incidence of levitation illusions depends not only on the field of view but also on the visible scene content.

关键词： Visual orientation self tilt perceived orientation gravitational vertical

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Recent Progresses in the Inspection of Aerospace Components by Infrared Thermography

Recent Progresses in the Inspection of Aerospace Components ...

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17th World Conference on Non-Destructive Testing

作者： Clemente Ibarra-Castanedo Ermanno Grinzato Sergio Marinetti Paolo Bison Marc Genest Marc Grenier Jean-Marc Piau Abdelhakim Bendada Xavier Maldague Computer Vision and Systems Laboratory Department of Electrical and Computer EngineeringUniversité LavalQuebec CityCanada GIK 7P4 Istituto per le Tecnologie della Costruzione-Consiglio Nazionale delle Ricerche (ITC-CNR) Corso Stati Uniti4-35127PadovaItaly. Institute for Aerospace Research (IAR) National Research Council Canada (NRC)1200 Montreal RoadBldg.M-14Room 130OttawaONCanadaK1A 0R6 Computer Vision and Systems Laboratory Department of Electrical and Computer EngineeringUniversité LavalQuebec CityCanada 1IK 7P4 Computer Vision and Systems Laboratory Department of Electrical and Computer EngineeringUniversité LavalQuebec CityCanada G1K 7P4

＜正＞The use NonDestructive Testing and Evaluation （NDT＆E） techniques for the inspection of aerospace materials has progressively increase in the last few decades as commercial and military aircrafts exceed their initial design life. Aerospace components are typically made of aluminium,honeycomb structures, composites or fibre metal laminates （FML）,which are affected by different types of anomalies,namely:delaminations,disbonds,water ingress,node failure and core *** causes are either material contamination introduced during manufacture,***,solvents,moisture,oils,etc.;or by damages caused during in-flight operation,*** *** thermography techniques have proven to be an effective way to detect and,in many cases,to quantify the degree of surface and subsurface damage on such components. Several configurations have been proposed to achieve an active thermography inspection ranging from passive inspection,*** applying any external stimulation,to active approaches,in which an external source of energy is used to produce a thermal contrast between the non-defective and the defective material. The thermal stimulation can be delivered to the specimen surface by optical, mechanical,electromagnetic or other *** physics and the practical considerations behind these approaches are different in all cases,and the selection of one or another will depend on the specific application and the availability of the *** this paper,a review of recent developments on the thermographic inspection of aerospace materials is *** guidelines,supported with examples on real and academic specimens,are provided to illustrate the most suitable technique to be considered for some conventional applications.

关键词： Infrared thermography Fibre metal laminates Honeycomb structures Composites Aluminium

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A Comparative Study of Classification Techniques for Knowledge-Assisted Image Analysis

A Comparative Study of Classification Techniques for Knowled...

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International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS

作者： G. T. Papadopoulos K. Chandramouli V. Mezaris I. Kompatsiaris E. Izquierdo M. G. Strintzis Informatics and Telematics Institute Centre for Research and Technology Hellas Thessaloniki Greece Information Processing Laboratory Electrical & Computer Engineering Department Aristotle University of Thessaloniki Thessaloniki Greece Multimedia and Vision Research Group Queen Mary University of London London UK

In this paper, four individual approaches to region classification for knowledge-assisted semantic image analysis are presented and comparatively evaluated. All of the examined approaches realize knowledge-assisted analysis via implicit knowledge acquisition, i.e. are based on machine learning techniques such as support vector machines (SVMs), self organizing maps (SOMs), genetic algorithm (GA)and particle swarm optimization (PSO). Under all examined approaches, each image is initially segmented and suitable low-level descriptors are extracted for every resulting segment. Then, each of the aforementioned classifiers is applied to associate every region with a predefined high-level semantic concept. An appropriate evaluation framework has been employed for the comparative evaluation of the above algorithms under varying experimental conditions.

关键词： Image analysis Image segmentation Algorithm design and analysis Knowledge acquisition Machine learning Support vector machines Support vector machine classification Self organizing feature maps Genetic algorithms Particle swarm optimization

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