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Level Set Segmentation Using Statistical Shape Priors

Level Set Segmentation Using Statistical Shape Priors

引用

ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： A.S. El-Baz A.A. Farag H.A. El Munim S.E. Yuksel Computer Vision & Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

A novel and robust 3-D segmentation approach is proposed using level sets based on shape constraints. The approach depends on both the gray level and shape information. A partial differential equation (PDE) is developed to control the evolution of the level sets. The PDE does not include weighting coefficients to be tuned, overcoming the disadvantages of other PDE approaches. The shape information is gathered from a set of the signed distance maps representing the training data as a histogram of the occurrences of the points inside and outside the object. We use a novel statistical approach to get a probability density function (pdf) for the signed distance map of the points inside and outside and also the distribution of gray level inside and outside the object. The proposed statistical approach is based on modelling the empirical density function (normalized histogram of occurrence) for either the gray level distribution or signed distance map with a linear combination of Gaussians (LCG) with positive and negative components. We modify an Expectation-Maximization (EM) algorithm to deal with the LCGs and also propose a novel EM-based sequential technique to get a close initial LCG approximation for the modified EM algorithm to start with. The pdf’s of the signed distance and intensity gray level are embedded in the speed function of the level set specifying the direction of evolution. Experimental results show how the approach is accurate in segmenting different types of 2-D and 3-D data sets including medical images.

关键词： Level set Shape Histograms Approximation algorithms Robustness Partial differential equations Training data Probability density function Density functional theory Gaussian distribution

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Germination of the Active Lighting : An Introduction and Brief History of Our Research

Germination of the Active Lighting : An Introduction and Bri...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： S. Hiura K. Sato I. Kanaya Osaka University Toyonaka Osaka Japan

We have been engaged in the researches on the active lighting techniques for twenty years. At first, we proposed a method to measure the 3-D shape of the object by projecting multiple patterns of structured light, because it is much faster than the method with scanning slit of light, and dense range image can be measured. For this purpose, we made a projector which consists of mechanicallychangeable masks, but it was soon replaced by a speciallymade liquid crystal panel with many slit segments. From the fact, we can proudly declare that the projector is not a diverted device but exclusively developed as a part of projector-camera systems, and the projection target is originally not a planar screen but a real scene with varied depth. Actually, this infant device was successful and commercially enough practical for 3-D shape measurement, but unfortunately we had to wait for the evolution of panel display technology more than a decade, to make a step to the studies which utilizes full duality between cameras and projectors. In the middle of 1990s, many researchers started using video projectors. Since we were computer vision researchers, we used the flexibility of video projector not for a interaction technique but improving performance of 3-D measurement such as motion tracking. But we were also aware of its advantage as a visualization tool in a real scene. Alike to the other research activities, we have confirmed that the projector can change the seen color, texture and specular of the real object. In addition, faked shade projected on the object make it possible to change our interpretation of its shape. Furthermore, the traditional shape measurement method we had developed is seamlessly combined with the visualization technique. Therefore, we have a common view to the possibility of intuitive interface systems with realistic visualization for communicating, training and designing works, so now is a good time to look-ing back on the history of projector-camera syst

关键词： History Shape measurement Visualization Layout Liquid crystals Image segmentation computer displays Cameras computer vision Motion measurement

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Characterizing fMRI Activations within Regions of Interest (ROIs) Using 3D Moment Invariants

Characterizing fMRI Activations within Regions of Interest (...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： B. Ng R. Abugharbieh Xuemei Huang M.J. McKeown Department of Electrical and Computer Engineering Pacific Parkinson's Research Center University of British Columbia Vancouver BC Canada Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada Department of Neurology School of Medicine University of North Carolina Chapel Hill NC USA Department of Medicine (Neurology) Pacific Parkinson's Research Center University of British Columbia Vancouver BC Canada

A novel method is proposed for characterizing spatial distribution changes in functional magnetic resonance imaging (fMRI) activation statistics under different experimental conditions. The proposed technique, based on three dimensional (3D) invariant moment descriptors, was applied to fMRI data recorded from eight healthy subjects performing internally or externally-cued finger tapping sequences. Voxel-based activation statistics were characterized in several regions of interest (ROIs), including the supplementary motor area (SMA), cerebellum, primary motor cortex, prefrontal cortex, and caudate. Examining the activation patterns of these neural regions using 3D moment invariants revealed that the patterns of activation regions were significantly different during externally and internally cued tasks when computed across subjects. In contrast, traditional methods that are based on amplitude of the activation statistics demonstrated reduced discriminability. The results suggest that the spatial distribution of activation is a more sensitive measure of activation changes, and complements conventional fMRI analyses.

关键词： Magnetic heads Filtering Low pass filters Nonlinear filters Linear discriminant analysis Biomedical imaging Nervous system Fingers Coils Smoothing methods

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Specifying, Interpreting and Detecting High-level, Spatio-Temporal Composite Events in Single and Multi-Camera Systems

Specifying, Interpreting and Detecting High-level, Spatio-Te...

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： S. Velipasalar L.M. Brown A. Hampapur Electrical Engineering Department Princeton University Princeton NJ USA IBM Thomas J. Watson Research Center Hawthorne NY USA

Detecting and tracking moving objects are important and challenging problems which have attracted much attention from the research community. However, in most cases, it is not enough to only track the objects. The goal should be to detect the occurrences of events of interest, which is important for applications such as video surveillance, video browsing and indexing. Yet, event detection introduces the challenge of providing the flexibility to specify customized events with varying complexity, and entering them to a system in a generic way. The event definitions should not be pre-defined and hard-coded. We introduce a spatio-temporal event detection system which lets the users to specify multiple composite events of high-complexity, and then detects their occurrence automatically. Events can be defined on a single camera view or across multiple camera views. Semantically higher level event scenarios can be built by using the building blocks, which we call the primitive events, and combining them by operators. More importantly, the newly defined composite events can be combined with each other. This layered structure makes the definition of events with higher and higher complexity possible. The event definitions are written to an XML file, which is then parsed and communicated to the tracking engines running on the videos of the corresponding cameras. With the proposed system, we have reached the next level and managed to go from detecting "a person exiting the building" to detecting "a person coming from the south corridor of the building and then exiting the building".

关键词： Event detection Object detection Cameras Video surveillance computer languages Indexing XML Engines Statistics Monitoring

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Euclidean Structure from Confocal Conics: Theory and Application to Camera Calibration

Euclidean Structure from Confocal Conics: Theory and Applica...

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conference on computer vision and pattern recognition (CVPR)

作者： P. Gurdjos Jun-Sik Kim In-So Kweon UPS IRIT-TCI Toulouse France Department of EECS KAIST Daejeon South Korea

ISBN: (纸本)0769525970

Plane-based calibration is now a very popular procedure because of its flexibility. One key step consists in detecting a set of coplanar features, from which the Euclidean structure of the corresponding 3D plane has to be computed. We suggest to use confocal conics as calibration targets, as they offer undeniable advantages over other ones (e.g., points or lines) in terms of detection and estimation, especially in the presence of partial occlusion. We introduce important projective and Euclidean properties of the linear family of conics (i.e., the confocal conic range), spanned by two confocal conics. In particular, we rely on the fact that the circular point-envelope - a rank-2 conic that encodes the 2D Euclidean structure - is a degenerate member of any confocal conic range. This allows us to give closed-form solutions in three cases: one conic with known foci, two confocal conics with known product of ratios of semi axes, and two unknown confocal conics. The performances of the proposed algorithms (consisting of a few lines of Matlab-like code) show up high accuracies for both intrinsic and extrinsic camera parameters. In addition to experiments with synthetic data, a video sequence is processed, showing off the interest of using confocal conics as calibration targets, for augmented reality purposes.

关键词： Cameras Calibration Closed-form solution pattern matching computer vision Uninterruptible power systems computer languages Video sequences Augmented reality Solid modeling

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Multiple Cardiac Arrhythmia recognition Using Adaptive Wavelet Network

Multiple Cardiac Arrhythmia Recognition Using Adaptive Wavel...

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Annual International conference of the ieee Engineering in Medicine and Biology society (EMBC)

作者： Chia-Hung Lin Pei-Jarn Chen Yung-Fu Chen You-Yun Lee Tainsong Chen Department of Electrical Engineering Kao-Yuan Institute of Technology Kaohsiung Taiwan Institute of Biomedical Engineering National Cheng Kung University Tainan Taiwan Department of Electrical Engineering Southern Taiwan University of Technology Tainan Taiwan Department of Computer Science and Information Engineering Da-Yeh University Changhua Taiwan

This paper proposes a method for electrocardiogram (ECG) heartbeat pattern recognition using adaptive wavelet network (AWN). The ECG beat recognition can be divided into a sequence of stages, starting from feature extraction and conversion of QRS complexes, and then identifying cardiac arrhythmias based on the detected features. The discrimination method of ECG beats is a two-subnetwork architecture, consisting of a wavelet layer and a probabilistic neural network (PNN). Morlet wavelets are used to extract the features from each heartbeat, and then PNN is used to analyze the meaningful features and perform discrimination tasks. The AWN is suitable for application in a dynamic environment, with add-in and delete-off features using automatic target adjustment and parameter tuning. The experimental results obtained by testing the data of the MIT-BIH arrhythmia database demonstrate the efficiency of the proposed method

关键词： Adaptive systems Electrocardiography Heart beat Feature extraction pattern recognition computer vision Neural networks Wavelet analysis Data mining Performance analysis

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Multisensor based security robot system for intelligent building

Multisensor based security robot system for intelligent buil...

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2006 ieee International conference on Multisensor Fusion and Integration for Intelligent Systems, MFI

作者： Luo, Ren C. Lin, Tung Y. Chen, Hsin C. Su, Kuo L. IEEE

ISBN: (纸本)1424405661

Intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21 century. The most importance role of the intelligent building is security system. In the paper, we focus on the Are detection and intruder detection of the security system, and use intelligent security robot to guard the safety for life and wealth in the intelligent building. We propose an adaptive fusion method for fire detection, and uses smoke sensor, flame sensor and temperature sensor to detect fire occurred. In reality, the phenomenon of the fire may have smoke, flame and high temperature. Then we use rule based method to detect intruder, and fuse body sensors, ultrasonic sensors and IR sensors to detect intruder. Finally, we implement the fire detection system in the intelligent security robot (Chung-Cheng-I).If fire occurred, the security robot can find out the fire source using the fire detection system. In the intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. The intelligent security robot transmits the message of detection result to the user using GSM modern for fire event and intruder, and transmits the detection result to client computer through internet. © 2006 ieee.

关键词： Robots

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Image Registration in Intra-oral Radiography

Image Registration in Intra-oral Radiography

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Annual International conference of the ieee Engineering in Medicine and Biology society (EMBC)

作者： C.C. Leung K.L. Yiu W.K. Tsui K.Y. Zee Department of Electrical & Electronic Engineering University of Hong Kong Hong Kong China Faculty of Dentistry University of Hong Kong Hong Kong China

Image registration is one of the image processing methods which is widely used in computer vision, pattern recognition, and medical imaging. In digital subtraction radiography, image registration is one of the important prerequisites to match the reference and subsequent images. In this paper, we propose an automatic non-rigid registration method namely curvature-based registration that relies on a curvature based penalizing term and its application on dental radiography. The regularizing term of this intensity-based registration approach provides affine linear transformation so that pre-registration step is no longer necessary. This leads to faster and more reliable solutions. The implementation of this approach is based on the numerical solution of the underlying Euler-Lagrange equations. In addition, a comparison between this algorithm and linear alignment method (LAM) with 20 image pairs is presented

关键词： Image registration Diagnostic radiography Dentistry Biomedical imaging Equations Application software Bone diseases Image processing computer vision Medical diagnostic imaging

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Notice of Violation of ieee Publication Principles: A Low Cost Embedded Color vision System Based on SX52

Notice of Violation of IEEE Publication Principles: A Low Co...

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International conference on Information and Automation (ICIA)

作者： Dong Li Yunsheng Jiang Guiyou Chen School of Engineering and Technology Shandong University of Technology Zibo Shandong China School of Control Science and Engineering Shandong University Jinan Shandong China

Notice of Violation of ieee Publication Principles "A Low Cost Embedded Color vision System Based on SX52" by Dong Li, Yunsheng Jiang, Guiyou Chen, in the Proceedings of the 2006 ieee International conference on Information Acquisition, August 20-23, 2006 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of ieee's Publication Principles. This paper is a duplication of the original text from the paper cited below. The original text was copied without attribution and without permission. Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article: "A Simple Low-cost Color vision System" by Anthony Rowe, Charles Rosenberg, Illah Nourbakhsh, in the Tech Sketch paper presented at the ieee computer vision and pattern recognition 2001 We describe a low cost embedded vision system in this paper. The goal of the system is to provide simple vision capabilities to small embedded systems in the form of an intelligent sensor. The system utilizes a low cost CMOS color camera module, a frame buffer chip and all image data is processed by a low cost microcontroller SX52. The system includes the essential functionality of color blob tracking, and improves upon it with tracking speeds of up to 50 frames per second. Other improvements were also made to facilitate communication with slower speed processors, as is often the case in a variety of robotics applications, including miniature robotics, hobby robotics and aerial robots.

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Information-Theoretic Feature Detection in Ultrasound Images

Information-Theoretic Feature Detection in Ultrasound Images

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Annual International conference of the ieee Engineering in Medicine and Biology society (EMBC)

作者： Greg Slabaugh Gozde Unal Ti-Chiun Chang Siemens Corporate Research Inc. Princeton NJ USA

The detection of image features is an essential component of medical image processing, and has wide-ranging applications including adaptive filtering, segmentation, and registration. In this paper, we present an information-theoretic approach to feature detection in ultrasound images. Ultrasound images are corrupted by speckle noise, which is a disruptive random pattern that obscures the features of interest. Using theoretical probability density functions of the speckle intensity distributions, we derive analytic expressions that measure the distance between distributions taken from different regions in an ultrasound image and use these distances to detect features. We compare the technique to classic gradient-based feature detection methods

关键词： computer vision Ultrasonic imaging Speckle Biomedical image processing Adaptive filters Image segmentation Probability density function Image analysis Density measurement Ultrasonic variables measurement

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