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International Conference on intelligent and Advanced systems, ICIAS

作者： Mahdi Ramezani Amin Heidari Emad Fatemizadeh Hamid Soltanian-Zadeh Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearest-neighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Clustering algorithms Algorithm design and analysis Correlation Approximation methods Independent component analysis Time series analysis Approximation algorithms

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Grasping simulation of an underactuated finger mechanism for larm hand

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International Journal of Modelling and Simulation 2010年第1期30卷 87-97页

作者： Yao, S. Wu, L. Ceccarelli, M. Carbone, G. Lu, Z. School of Automation Science and Electrical Engineering Beihang University Beijing China College of Information Engineering Central University for Nationalities Beijing China State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing China Beijing University of Aeronautics and Astronautics China and University of Cassino Italy LARM: Laboratory of Robotics and Mechatronics Cassino United States

In this paper, the grasp operation of an underactuated finger mechanism is simulated with the aim to characterize and analyze its performance. The design of the proposed mechanism is based on spring systems that give suitable underactuation characteristics. A CAD model is proposed and then it is used in a procedure for numerical simulation. Simulation results show suitable capability for grasping a wide range of objects in size and shape by operating the mechanism inside the finger body. The achieved grasp has been simulated as a human-like functionality with a grasp contact in each phalanx.

关键词： computer aided design

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Multiple-atlas-based automatic sementation of hippocampus for lateralization in temporal lobe epilepsy

Multiple-atlas-based automatic sementation of hippocampus fo...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi-Asl Kourosh Jafari-Khouzani Hamid Soltanian-Zadeh Image Analysis Laboratory Department of Diagnostic Radiology Henry Ford Health System Detroit MI USA School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424441259

We introduce a 3D segmentation framework which uses principal shapes. The probabilistic energy function of the method is defined based on intensity, tissue type, and location information of the structures using a multiple atlas method. For intensity information, nonparametric probability density function is used which considers intensity relation of different structures. To find a local minimum of the energy function, a two-step optimization strategy is used. In the first step, shape parameters are optimized based on the analytic derivatives of the energy function. In the second step, shapes of the structures are fine-tuned using a level set method. The proposed method is shown to be superior to some popular methods in the literature using a dataset of 64 patients with mesial temporal lobe epilepsy. In addition, the method can be used for lateralization with accuracy close to that of manual segmentation.

关键词： Hippocampus Temporal lobe Epilepsy Image segmentation Principal component analysis Shape control Probability density function Level set Skull Algorithm design and analysis

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Fuzzy controller for cooperative object pushing with variable line contact

Fuzzy controller for cooperative object pushing with variabl...

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International Conference on Mechatronics (ICM)

作者： Mahsa Aliakbar Golkar Sarah Taghavi Namin Hossein Aminaiee Control and Intelligent Processing Center of Excellence Robotics and AI Laboratory Department of Electrical and Computer Engineering University of Tehran Iran

Designing an appropriate cooperation protocol in multi-robot systems such as multi-robot object manipulation systems is a challenging task. In this paper designing and implementing a cooperation protocol between two robots pushing an object toward an arbitrary goal configuration is investigated. The proposed method benefits from task decoupling which simplifies the cooperation protocol design. Each robot gets its proper action from a particular fuzzy inference system independently. The fuzzy controllers outputs are low-level robot commands by which the need to a robot path planning algorithm is eliminated. Simulation results show that robots could push the object to the goal configuration cooperatively. Experiments have been conducted to approve the proposed system.

关键词： Fuzzy control Robot kinematics Protocols Fuzzy systems Electric variables control Control systems Multirobot systems Path planning Inference algorithms Mobile robots

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Cooperative mapping of multiple PTZ cameras in automated surveillance systems

Cooperative mapping of multiple PTZ cameras in automated sur...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Chung-Chen Chen Yi Yao Anis Drira Andreas Koschan Mongi Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering & Computer Science University of Tennessee Knoxville TN USA

Due to the capacity of pan-tilt-zoom (PTZ) cameras to simultaneously cover a panoramic area and maintain high resolution imagery, researches in automated surveillance systems with multiple PTZ cameras have become increasingly important. Most existing algorithms require the prior knowledge of intrinsic parameters of the PTZ camera to infer the relative positioning and orientation among multiple PTZ cameras. To overcome this limitation, we propose a novel mapping algorithm that derives the relative positioning and orientation between two PTZ cameras based on a unified polynomial model. This reduces the dependence on the knowledge of intrinsic parameters of PTZ camera and relative positions. Experimental results demonstrate that our proposed algorithm presents substantially reduced computational complexity and improved flexibility at the cost of slightly decreased pixel accuracy, as compared with the work of Chen and Wang. This slightly decreased pixel accuracy can be compensated by consistent labeling approaches without added cost for the application of automated surveillance systems along with changing configurations and a larger number of PTZ cameras.

关键词： Surveillance Costs Robot vision systems Smart cameras Computational complexity intelligent robots Image resolution Polynomials Labeling Simultaneous localization and mapping

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MIMO antenna optimization using method of moments analysis

MIMO antenna optimization using method of moments analysis

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International Workshop on Antenna Technology: Small Antennas and Novel Metamaterials, iWAT

作者： Mehrbod Mohajer Safieddin Safavi-Naeini The intelligent Multi-Antenna Radio System (iMARS) Laboratory Department of Electrical & Computer Engineering University of Waterloo Waterloo ONT Canada

A MIMO antenna design optimization method based on minimization of correlation coefficients for maximizing the system capacity in multiple-input multiple-output (MIMO) systems is presented. The packaging effects on radiation field patterns of MIMO antenna elements have also been included using a reciprocity approach and method of moments (MoM) analysis. As practical examples, optimal location of two patch antennas placed on a small ground plane and conducting cube have been determined using the proposed method.

关键词： MIMO Optimization methods Moment methods Packaging Radio transmitters Receiving antennas Transmitting antennas Signal to noise ratio Power system modeling Patch antennas

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ANFIS Controller with Fuzzy Subtractive Clustering Method to Reduce Coupling Effects in Twin Rotor MIMO system (TRMS) with Less Memory and Time Usage

ANFIS Controller with Fuzzy Subtractive Clustering Method to...

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International Conference on Advanced computer Control, ICACC

作者： Thair Sh. Mahmoud Mohammed H. Marhaban Tang S. Hong Sokchoo Ng Department of Electrical and Electronic Engineering Faculty of Engineering UPM Selangor Darul Ehsan Malaysia Department of Mechanical and Manufacturing Engineering Institute of Advanced Technology UPM Selangor Darul Ehsan Malaysia Intelligent System and Robotics Laboratory Institute of Advanced Technology UPM Selangor Darul Ehsan Malaysia

In this paper, adaptive neural fuzzy inference system (ANFIS) and fuzzy subtractive clustering method (FSCM) were used to solve non-linearity, trajectory, and interaction problems of twin rotor MIMO system (TRMS). Basically, four fuzzy logic controllers (FLC) have been proposed to match the control objectives on TRMS. The four FLCs are considered as high consumers of memory and processing time relatively. New developed controllers are extracted to cope with these problems with less memory and time. Learning data were extracted from training the used conventional FLCs. Simulation results under MATLAB/Simulinkreg proved the improvement of response and simplicity of controller.

关键词： Control systems Fuzzy control Fuzzy systems Clustering methods MIMO Transmission line measurements Data mining Power capacitors Fuzzy logic MATLAB

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Dynamic Node Collaboration for Mobile Target Tracking in Wireless Camera Sensor Networks

Dynamic Node Collaboration for Mobile Target Tracking in Wir...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： L. Liu X. Zhang H. Ma Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and Telecommunications Beijing China Networking and Information System Laboratory Department of Electrical and Computer Engineering Texas A and M University College Station TX USA

ISBN: (纸本)9781424435128

Compared to the other types of sensor networks, the wireless camera sensor networks can offer much more comprehensive and accurate information in mobile target tracking applications. We propose a dynamic node collaboration scheme for mobile target tracking in wireless camera sensor networks. Unlike the traditional sensing models, we develop a nonlinear localization-oriented sensing model for camera sensors by taking the perspective projection and the observation noises into account. Based on our sensing model, we apply the sequential Monte Carlo (SMC) technique to estimate the belief state of the target location. In order to implement the SMC based tracking mechanism efficiently, we propose a dynamic node collaboration scheme, which can balance the tradeoff between the quality of tracking and the network cost. Our scheme deploys the dynamic cluster architecture which mainly includes the following two components. First, we design a scheme to elect the cluster heads during the tracking process. Second, we develop an optimization-based algorithm to select an optimal subset of camera sensors as the cluster members for estimating the target location cooperatively. Also conducted is a set of extensive simulations to validate and evaluate our proposed schemes.

关键词： Wireless sensor networks Collaboration Target tracking Cameras intelligent sensors Vehicle dynamics Peer to peer computing Image sensors Sensor phenomena and characterization Sliding mode control

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Camera handoff with adaptive resource management for multi-camera multi-target surveillance

Camera handoff with adaptive resource management for multi-c...

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IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008

作者： Chen, Chung-Hao Yi, Yao Page, David Abidi, Besma Koschan, Andreas Abidi, Mongi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN 37996 United States GE Global Research Center Niskayuna NY 12309 United States

ISBN: (纸本)9780769533414

Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentrate on data association, namely consistent labeling, where images of the same object are matched across different cameras. However, most real-time object tracking systems see a decrease in the system's frame rate as the number of tracked objects increases. To address this issue, we propose to incorporate an adaptive resource management mechanism into camera handoff. In so doing, cameras' resources can be dynamically allocated to multiple objects according to their priorities and hence the required minimum frame rate can be maintained. Experimental results illustrate that the proposed camera handoff algorithm is capable of maintaining a constant frame rate and of achieving a substantially improved handoff success rate by approximately 20% in comparison with the algorithm presented by Khan and Shah. © 2008 IEEE.

关键词： Cameras

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Camera Handoff with Adaptive Resource Management for Multi-camera Multi-target Surveillance

Camera Handoff with Adaptive Resource Management for Multi-c...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Chung-Hao Chen Yi Yao David Page Besma Abidi Andreas Koschan Mongi Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA GE Global Research Center Niskayuna NY USA

Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentrate on data association, namely consistent labeling, where images of the same object are matched across different cameras. However, most real-time object tracking systems see a decrease in the system's frame rate as the number of tracked objects increases. To address this issue, we propose to incorporate an adaptive resource management mechanism into camera handoff. In so doing, cameras¿ resources can be dynamically allocated to multiple objects according to their priorities and hence the required minimum frame rate can be maintained. Experimental results illustrate that the proposed camera handoff algorithm is capable of maintaining a constant frame rate and of achieving a substantially improved handoff success rate by approximately 20% in comparison with the algorithm presented by Khan and Shah.

关键词： Resource management Surveillance Labeling Real time systems intelligent robots USA Councils Videoconference Robot vision systems Smart cameras Robot kinematics

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