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检索条件"机构=Image Processing and Multimedia Laboratory Department of Electrical & Computer Engineering"

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Face recognition through mismatch driven representations of the face

Face recognition through mismatch driven representations of ...

引用

Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance

作者： S. Lucey Tsuhan Chen Advanced Multimedia Processing Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

Performance of face verification systems can be adversely affected by a number of different mismatches (e.g. illumination, expression, alignment, etc.) between gallery and probe images. In this paper, we demonstrate that representations of the face used during the verification process should be driven by their sensitivity to these mismatches. Two representation categories of the face are proposed, parts and reflectance, each motivated by their own properties of invariance and sensitivity to different types of mismatches (i.e. spatial and spectral). We additionally demonstrate that the employment of the sum rule gives approximately equivalent performance to more exotic combination strategies based on support vector machine (SVM) classifiers, without the need for training on a tuning set. Improved performance is demonstrated, with a reduction in false reject rate of over 30% when compared to the single representation algorithm. Experiments were conducted on a subset of the challenging face recognition grand challenge (FRGC) v1.0 dataset.

关键词： Face recognition Lighting Probes Reflectivity Employment Support vector machines Support vector machine classification multimedia systems Laboratories Surveillance

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Dynamic Semantic Identification with Complexity Constraints as a Knapsack Problem

Dynamic Semantic Identification with Complexity Constraints ...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： M. Falelakis C. Diou A. Valsamidis A. Delopoulos Multimedia Understanding Group Information Processing Laboratory Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece

The process of automatic identification of high level semantic entities (e.g., objects, concepts or events) in multimedia documents requires processing by means of algorithms that are used for feature extraction, i.e. low level information needed for the analysis of these documents at a semantic level. This work copes with the high and often prohibitive computational complexity of this procedure. Emphasis is given to a dynamic scheme that allows for efficient distribution of the available computational resources in application. Scenarios that deal with the identification of multiple high level entities with strict simultaneous restrictions, such as real time applications

关键词： Data mining Feature extraction Algorithm design and analysis Computational efficiency Encyclopedias Information processing Laboratories Information analysis Text analysis Computational complexity

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Acousto-optics with MATLAB®

Acousto-optics with MATLAB&reg

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Acousto-optics and Photoacoustics

作者： Poon, Ting-Chung Kim, Taegeun Optical Image Processing Laboratory Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA 24061 United States Department of Optical Engineering Sejong University 98 Kunja-Dong Kwangjin-Ku Seoul 143-747 Korea Republic of

MATLAB&reg is a widely accepted software tool routinely used in engineering, but not so much in applied optics and especially in acousto-optics. In this talk, we first explore the use of MATLAB&reg to solve so... 详细信息

MATLAB® is a widely accepted software tool routinely used in engineering, but not so much in applied optics and especially in acousto-optics. In this talk, we first explore the use of MATLAB® to solve some well-known examples in acousto-optics such as Bragg diffraction and Raman-Nath diffraction. After establishing the correctness of the MATLAB® approach, we then apply it to investigate image processing using acousto-optics and complete power transfer into the second and third Bragg order.

关键词： computer aided software engineering

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Using a Free-Parts Representation for Visual Speech Recognition

Using a Free-Parts Representation for Visual Speech Recognit...

引用

Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： P. Lucey S. Lucey S. Sridharan Queensland University of Technology Speech Audio Image and Video Research Laboratory Brisbane Australia Advanced Multimedia Processing Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

Motivated by the success of free-parts based representations in face recognition, we have attempted to address some of the problems associated with applying such a philosophy to the task of speaker-independent visual speech recognition. A major problem with canonical area-based approaches in automatic visual speech recognition is the dependence these approaches have on locating and tracking the speaker’s region of interest (ROI) correctly. By employing a free-parts representation,we assume that the position/structure of patches within the mouth image can be relaxed so they can "freely" move to varying extents, hence reducing the influence of the front-end effect. In this paper, we show that by using a free-parts representation we gain some robustness against the problem of ROI localisation and tracking compared to current area-based feature extraction techniques such as the discrete cosine transform (DCT). Also in this paper, we expose the importance of representation for the task of visual speech recognition highlighted by the poor results current representations yield.

关键词： Speech recognition Mouth Hidden Markov models Laboratories Face recognition Feature extraction Discrete cosine transforms Robustness Automatic speech recognition Pixel

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Variational-based method to extract parametric shapes from images

Variational-based method to extract parametric shapes from i...

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International Conference on computer Vision (ICCV)

作者： M.T. El-Melegy N.H. Al-Ashwal A.A. Farag Electrical Engineering Department Assiut University Asyut Egypt Computer Vision and Image Processing Laboratory University of Louisville KY USA

In this paper, we propose a variational method to segment image objects, which have a given parametric shape based on a level-set formulation of the Mumford-Shah functional, and the shape parameters. We define an energy functional composed by two complementary terms. The first one detects object boundaries using a Chan-Vese-like method. The second term constrains the contour to find a shape compatible with the parametric shape. The segmentation of the object of interest is given by the minimum of our energy functional. This minimum is computed with the calculus of variation and the gradient descent method that provide a system of evolution equations solved with the well-known level set method. We focus in this paper on the parametric category of image linear objects. Applications of the proposed model are presented on synthetic and real images

关键词： Shape image segmentation Level set computer vision Focusing image processing Object detection Calculus Application software Equations

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3D ROC analysis for medical imaging diagnosis

3D ROC analysis for medical imaging diagnosis

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2005 27th Annual International Conference of the engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Wang, Su Chang, Chein-I Yang, Sheng-Chih Hsu, Giu-Cheng Hsu, Hsian-He Chung, Pau-Choo Guo, Shu-Mei Lee, San-Kan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 Department of Electrical Engineering National Cheng Kung University Taiwan Department of Radiology Tri-Service General Hospital National Defense Medical Center Taipei 114 Taiwan Department of Computer Science and Information Engineering National Cheng Kung University Taiwan Administrative Office Suao Veterans Hospital Yuan County 270 Taiwan

ISBN: (纸本)0780387406

Receiver operating characteristics (ROC) has been widely used as a performance evaluation tool to measure effectiveness of medical modalities. It is derived from a standard detection theory with false alarm and detection power interpreted as false positive (FP) and true positive (TP) respectively in terms of medical diagnosis. The ROC curve is plotted based on TP versus FP via hard decisions. This paper presents a three dimensional (3D) ROC analysis which extends the traditional two-dimensional (2D) ROC analysis by including a threshold parameter in a third dimension resulting from soft decisions, (SD). As a result, a 3D ROC curve can be plotted based on three parameters, TP, FP and SD. By virtue of such a 3D ROC curve three two-dimensional (2D) ROC curves can be derived, one of which is the traditional 2D ROC curve of TP versus FP with SD reduced to hard decision. In order to illustrate its utility in medical diagnosis, its application to magnetic resonance (MR) image classification is demonstrated. © 2005 IEEE.

关键词： Medical imaging

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A low-level approach to semantic classification of mobile multimedia content

A low-level approach to semantic classification of mobile mu...

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The 2nd European Workshop on the Integration of Knowledge, Semantics and Digital Media Technology, 2005. EWIMT 2005. (Ref. No. 2005/11099)

作者： A. Mariappan M. Igarta C. Taskiran B. Gandhi E.J. Delp Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Multimedia Research Lab Motorola Research Laboratories Schaumburg IL USA

Pseudo-semantic labeling is a novel approach to organize mobile multimedia content such as images and videos. We have developed low-complexity algorithms to derive labels, such as "indoor/outdoor", "face/not face", that can be run on the mobile device. "Indoor/outdoor" classification is done based on the presence of sky in the images. Skin like pixels are detected based on the color information and if present they are matched to a pre-defined "facetemplate" to detect the presence of faces in images. We have developed an initial framework for finding the degree of blurriness in an image, which can be used for labels like "blurry/not blurry".

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Clustering by principal curve with tree structure

Clustering by principal curve with tree structure

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International Symposium on Signals, Circuits and Systems (ISSCS)

作者： I. Cleju P. Franti Xiaolin Wu Multimedia Signal Processing Group Department of Computer and Information Science University of Karlsruhe Konstanz Germany Speech and Image Processing Research Group Department of Computer Science University of Joensuu Joensuu Finland Multimedia Computing and Comucations Laboratory Department of Etectrical and Computer Engineering McMaster University Hamilton ONT Canada

Data clustering is intensively used in signal processing in tasks such as multimedia compression, segmentation and pattern matching. In this work we extend the use of principal curves in clustering to complex multidimensional datasets. The use of principal curve in clustering is limited for high complexity data. Automatic parameterization of the principal curve to assure good results for different datasets is a difficult task. We propose to use the tree structure to capture the general settlement of the data. Using this topology, regions of the dataset can be extracted, individually clustered using the principal curve and then optimally recombined. The experiments show the improvement of the new method over the principal curve based clustering and the good performance compared to other clustering methods.

关键词： Tree data structures Clustering algorithms Partitioning algorithms multimedia computing Quantization computer science Pattern matching Data mining Application software Information science

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Characterization of a cascade LMS predictor

Characterization of a cascade LMS predictor

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： D.Y. Huang X. Su A. Nallanathan Multimedia Signal Processing Laboratory/Media Division Institute for Infocomm Research Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore

An FIR cascade structure for adaptive linear prediction is studied in which each stage FIR filter is independently adapted using an LMS algorithm. Theoretical analysis shows that the cascade performs a linear prediction in a way of successive refinement and each stage tries to obliterate the dominant mode of its input. Experimental results show that the performance of the cascade LMS predictor are in good agreement with our theoretical analysis.

关键词： Least squares approximation Finite impulse response filter Convergence Performance analysis Signal analysis Adaptive signal processing Laboratories Signal processing algorithms Speech coding Video coding

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3D ROC analysis for detection software used in water monitoring

3D ROC analysis for detection software used in water monitor...

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Chemical and Biological Standoff Detection III

作者： Liu, Wei-Min Wang, Su Chang, Chein-I. Jensen, Janet L. Jensen, James O. Knapp, Harlan Daniel, Robert Yin, Ray Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 US Army Edgewood Chemical and Biological Center Aberdeen Proving Ground MD 21010 ANP Technologies Inc. 824 Interchange Boulevard Newark DE 19711

Under the U.S. Army sponsored Joint Service Agent Water Monitor (JSAWM) program, developing hand-held assays using tickets for chemical/biological agent detection has been of major interest. One of keys to success is to develop detection algorithms that not only can effectively detect the presence of various agents, but also can quantify the detected agents. This paper presents a recent development of detection software that can perform 3-dimensional (3D) receiver operating characteristics (ROC) analysis which is based on quantified agent concentration. The ROC curves have been widely used in communications, signal processing and medical communities to evaluate the effectiveness of a detection technique. It generally formulates a signal detection problem as a binary composite hypothesis testing problem with the null hypothesis and the alternative hypothesis represents the case of no signal and the case of signal presence respectively. The ROC curve is then plotted based on the detection probability (power) PD versus the false alarm probability, P F. Unfortunately, such a two-dimensional (2D) (PD,P F)-based ROC curve does not factor in the concentration detected in an agent signal which is a crucial parameter in chemical/biological agent detection. The proposed 3D ROC analysis is developed from such a need. It includes an additional parameter, referred to as threshold t, which is used to threshold the detected agent signal concentration. Consequently, a different value of t results in a different 2D ROC curve. In order to take into account the thresholding factor t, a 3D ROC curve is derived and plotted based on three parameters, (PD,PF,t). As a result of the 3D ROC curve, three 2D ROC curves can be also derived. One is the conventional 2D (P D,PF)-ROC curve. Another is a 2D (PD,t)-ROC curve which describes the relationship between PD and the threshold value t. A third one is a 2D (PF,t)-ROC curve which shows the effect of the threshold value t on PF. The utility of

关键词： computer software

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