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Multi-Modal Human Verification Using Face and Speech

Multi-Modal Human Verification Using Face and Speech

引用

IEEE International Conference on Computer Vision systems (ICVS)

作者： Changhan Park Joonki Paik Taewoong Choi Soonhyob Kim Youngouk Kim J. Namkung Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Multimedia Signal Processing Laboratory Kwangwoon University Seoul South Korea Precision Machinery Center Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University Seoul South Korea

In this paper, we propose a personal verification method using both face and speech to improve the rate of single biometric verification. False acceptance rate (FAR) and false rejection rate (FRR) have been a fundamental bottleneck of real-time personal verification. The proposed multimodal biometric method is to improve both verification rate and reliability in real-time by overcoming technical limitations of single biometric verification methods. The proposed method uses principal component analysis (PCA) for face recognition and hidden markov model (HMM) for speech recognition. It also uses fuzzy logic for the final decision of personal verification. Based on experimental results, the proposed system can reduce FAR down to 0.0001%, which provides that the proposed method overcomes the limitation of single biometric system and provides stable personal verification in real-time.

关键词： Humans Speech Face detection Face recognition Biometrics Principal component analysis Feature extraction Hidden Markov models image edge detection Laboratories

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Multimodal priority verification of face and speech using momentum back-propagation neural network

引用

3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Park, Changhan Ki, Myungseok Namkung, Jaechan Paik, Joonki Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-dong Tongjak-Ku Seoul 156-756 Korea Republic of Broadcasting Media Research Group Digital Broadcasting Research Division ETRI 161 Gajeong-dong Yuseong-Gu Daejeon 305-700 Korea Republic of Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of

ISBN: (纸本)3540344373

In this paper, we propose a priority verification method for multimodal biometric features by using a momentum back-propagation artificial neural network (MBP-ANN). We also propose a personal verification method using both face and speech to improve the rate of single biometric verification. False acceptance rate (FAR) and false rejection rate (FRR) have been a fundamental bottleneck of real-time personal verification. The proposed multimodal biometric method is to improve both verification rate and reliability in real-time by overcoming technical limitations of single biometric verification methods. The proposed method uses principal component analysis (PCA) for face recognition and hidden markov model (HMM) for speech recognition. It also uses MBPANN for the final decision of personal verification. Based on experimental results, the proposed system can reduce FAR down to 0.0001%, which proves that the proposed method overcomes the limitation of single biometric system and proves stable personal verification in real-time. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Neural networks

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Multi-modal human verification using face and speech

Multi-modal human verification using face and speech

引用

Fourth IEEE International Conference on Computer Vision systems, ICVS'06

作者： Park, Changhan Choi, Taewoong Kim, Youngouk Kim, Soonhyob Namkung, Jaechan Paik, Joonki Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-dong Tongjak-Ku Seoul 156-756 Korea Republic of Multimedia Signal Processing Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of Precision Machinery Center Korea Electronics Technology Institute 401-402 B/D 193 Yakdae-dong Wonmi-Gu Puchon Kyunggido 420-140 Korea Republic of

ISBN: (纸本)0769525067

关键词： Face recognition

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High SNR flexible top hat monopole probe for 1.5 T MRI

High SNR flexible top hat monopole probe for 1.5 T MRI

引用

作者： Mohammadzadeh, M. Shahabadi, M. Soltanian-Zadeh, H. Tavakoli, A. Rafiei, B. Javidnia, D. Oghabian, M.A. Department of Physics Amir-Kabir University of Technology Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Electrical Engineering Amir-Kabir University of Technology Tehran Iran Medical Imaging Center Imam Khomeyni Hospital Tehran Iran Research Center for Science and Technology in Medicine Tehran University of Medical Sciences Tehran Iran

In this paper, design principles and application of a thin and flexible intravascular top hat monopole probe with increased signal-to-noise ratio (SNR) and improved longitudinal and radial coverage are described and compared with the conventional monopole probe. The top hat probe is constructed by removing a segment of the shield of a coaxial cable. A flexible thin copper foil in contact with the inner conductor of the cable is added to the end section of the cable. The copper foil acts as an antenna top hat load increasing the uniformity of the current distribution on the probe and establishes a uniform region of SNR distribution around the probe. Improvement of the SNR distribution of the top hat probe relative to the conventional monopole probe is evaluated using quantitative indices. Experimental results show that for the top hat probe, the ratio of the maximum image SNR to its relative standard deviation (SR) is 2.73 times higher than that of a conventional probe. © 2006 IOP Publishing Ltd.

关键词： Medical imaging

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Optical flow-based tracking of deformable objects using a non-prior training active feature model 5th

Optical flow-based tracking of deformable objects using a no...

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5th Pacific Rim Conference on Multimedia, PCM 2004

作者： Kim, Sangjin Kang, Jinyoung Shin, Jeongho Lee, Seongwon Paik, Joonki Kang, Sangkyu Abidi, Besma Abidi, Mongi Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-Dong Tongjak-Ku Seoul156-756 Korea Republic of Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering The University of Tennessee KnoxvilleTN37996-2100 United States

ISBN: (纸本)9783540239857

This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed algorithm mainly focuses on analysis of deformable objects, and provides real-time, robust tracking. The proposed object tracking procedure can be divided into two steps: (i) optical flow-based tracking of feature points and (ii) NPT-AFM for robust tracking. In order to handle occlusion problems in object tracking, feature points inside an object are estimated instead of its shape boundary of the conventional active contour model (ACM) or active shape model (ASM), and are updated as an element of the training set for the AFM. The proposed NPT-AFM framework enables the tracking of occluded objects in complicated background. Experimental results show that the proposed NPT-AFM-based algorithm can track deformable objects in real-time. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Optical flows

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Plane identification and segmentation from uncalibrated stereo based on evolutionary approach

Plane identification and segmentation from uncalibrated ster...

引用

IEEE International Symposium on intelligent Signal processing and Communication systems (ISPACS)

作者： Junghoon Jung Taekyung Kim Ohyun Kwon Joonki Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)0780386396

Planes are widely used in various vision tasks due to their abundance especially in man-made environments. Assuming an uncalibrated stereo image acquisition system, we propose a new plane identification and segmentation algorithm using an evolutionary approach. The proposed algorithm enables faster and more robust estimation of the plane since it progressively searches the best solution in a guided direction. Experimental results show that the proposed algorithm has higher performance than the existing method.

关键词： image segmentation Iterative algorithms Evolutionary computation Robustness Transmission line matrix methods image processing intelligent systems Laboratories Multimedia systems Electronic mail

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Wavelet transform-based hierarchical active shape model for object tracking

Wavelet transform-based hierarchical active shape model for ...

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IEEE International Symposium on intelligent Signal processing and Communication systems (ISPACS)

作者： Hyunjong Ki Jeonho Shin Joonki Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)0780386396

This paper proposes a hierarchical approach to the active shape model (ASM) using a wavelet transform. Local structure model fitting in the ASM plays an important role in model-based pose and shape analysis. The proposed algorithm can robustly find good solutions in complex images by using wavelet decomposition. We also describe how to apply Kalman filtering for ASM-based, real-time video tracking. The proposed algorithm has been tested for various sequences containing human motion to demonstrate the improved performance of the proposed object tracking.

关键词： Active shape model Humans Robustness Kalman filters Filtering image analysis image processing intelligent systems Laboratories Multimedia systems

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Enhanced active shape model using evolutionary computation and its extension to RGB color space

Enhanced active shape model using evolutionary computation a...

引用

IEEE International Symposium on intelligent Signal processing and Communication systems (ISPACS)

作者： V. Maik Hyunjong Ki Sangjin Kim Jeongho Shin Seongwon Lee L. Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

This paper deals with an application of evolutionary computation to active shape model (ASM) for locating and analyzing objects an image. The ASM algorithm has proved to be a successful method for segmentation of objects in gray-scale images. However, a number of modifications and extensions to the basic ASM algorithm have been proposed to cope up with various limitations. The proposed method in this paper relies on two such extensions: (i) evolutionary algorithm for better local structure model; and (ii) incorporation of color information for solving the outlier problem in model fitting.

关键词： Active shape model Evolutionary computation Humans Biological system modeling Application software Deformable models Robustness Colored noise Noise shaping image processing

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Automatic face region tracking for highly accurate face recognition in unconstrained environments

Automatic face region tracking for highly accurate face reco...

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

作者： Y.-O. Kim J. Paik Jingu Heo A. Koschan B. Abidi M. Abidi Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Image Processing Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville USA

We present a combined real-time face region tracking and highly accurate face recognition technique for an intelligent surveillance system. High-resolution face images are very important to achieving accurate identification of a human face. Conventional surveillance or security systems, however, usually provide poor image quality because they use only fixed cameras to record scenes passively. We have implemented a real-time surveillance system that tracks a moving face using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction with the PTZ. Color information in the ROI is updated to extract features for optimal tracking and zooming. FaceIt/sup /spl reg//, which is one of the most popular face recognition software packages, is evaluated and then used to recognize the faces from the video signal. Experimentation with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

关键词： Face recognition Surveillance Real time systems Humans Cameras intelligent systems Security image quality Layout Low pass filters

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Dense range image smoothing using adaptive regularization

Dense range image smoothing using adaptive regularization

引用

IEEE International Conference on image processing

作者： Yiyong Sun Joon-Ki Paik J.R. Price M.A. Abidi Department of Electrical and Computer Engineering Imaging Robotics and Intelligent Systems Laboratory University of Tennessee Knoxville USA Department of Image Engineering Graduate School of Advanced Imaging Science Chung-Ang University Seoul South Korea

We propose an adaptive regularization algorithm for smoothing dense range images using a novel, first order stabilizing function. The stabilizer we suggest is based upon minimizing the reconstructed surface area and is derived in the native, spherical coordinate system of the range scanner. This allows adjustments to be made along only the direction of measurement, thereby preventing the data overlapping problem that can arise in dense images. Adaptation is achieved by adjusting the regularization parameter according to the results of 2D edge analysis. Results indicate effective noise suppression along with well preserved edges and details in the reconstructed, 3D surfaces.

关键词： Smoothing methods Surface reconstruction image reconstruction image edge detection intelligent robots Robot kinematics intelligent systems Laboratories Laser noise Noise measurement

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