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A Key Frame Selection-Based Facial Expression Recognition System

A Key Frame Selection-Based Facial Expression Recognition Sy...

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International Conference on Innovative Computing, Information and Control (ICICIC)

作者： S.M. Guo Y.A. Pan Y.C. Liao C.Y. Hsu J.S.H. Tsai C.I. Chang Department of Computer Science and Information Engineering National Engineering Kung University Tainan Taiwan Department of Computer Science and Information Engineering National Cheng-Kung University Tainan Taiwan Republic of China Department of Computer Science and Electrical Engineering University of Maryland Baltimore County (UMBC) Baltimore MD U.S.A. National Cheng Kung University Tainan TW Department of Electrical Engineering National Engineering Kung University Tainan Taiwan Department of Electrical Engineering National Cheng-Kung University Tainan Taiwan Republic of China Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore Baltimore MD USA

Automatic recognition of facial expressions has received considerable interest in the computer vision. This paper presents a key frame selection-based system for recognition of four basic facial expressions: happiness, anger, sadness and surprise, in image sequences. The proposed new approach is designed for recognition of facial expressions via a key frame selection of the facial motion from an image sequence where an optical flow is used to determine changes in a facial expression, experimental results demonstrate that the proposed automatic recognition process significantly improves the computational complexity encountered in facial expression recognition while enhancing the ability of recognition

关键词： Face recognition Face detection image recognition image sequences Feature extraction Facial features computer science Remote sensing Signal processing image processing

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3D ROC Analysis for Medical Imaging Diagnosis

3D ROC Analysis for Medical Imaging Diagnosis

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

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

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

关键词： image analysis Biomedical imaging Radar detection Medical diagnosis Detectors computer science Hospitals Medical diagnostic imaging Magnetic analysis Performance analysis

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Determination of the Grey Level Ranks for the Segmentation of Textured images

Determination of the Grey Level Ranks for the Segmentation o...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Z. Ameur A. Adane S. Ameur Faculty of Electrical Engineering and Computer Science Department of Electronics Laboratory of Random Phenomena Analysis and Modeling LAMPA Mouloud Mammeri University Tizi Ouzou Algeria Faculty of Electronics and Computer Science Department of Telecommunications Laboratory of Image Processing and Radiation University of Sciences and Technology of Algiers U. S. T. H. B. Bab-Ezzouar Algeria

In many cases, an image is made of various types of texture. Such diversity can be usefully exploited to get a suitable decomposition of the image into typical classes and then, identify its constitutive elements. Among the approaches used to segment textured images, those based on the statistical analysis of the neighborhood of each pixel seem to be most efficient. In this paper, this kind of method is implemented, which consists in coding the pixels surrounding each point of the image by taking into account the path traveling through them and their grey levels. The rank vectors namely the codes obtained for all the possible paths, are then classified using the K-means algorithm. Considering the 24- rank vectors, this method is tested on different images of the Brodatz album and compared with Laws filters and GLCM. It yields a satisfactory reproduction of the image contours and a classification ratio exceeding 98 %. The 24 rank based-method is also applied to meteorological images collected by Meteosat over Europe and North Africa during December 1994. It is found that these images can be segmented into eight typical classes assignable to the soils, the seas and the clouds observed in the regions under study.

关键词： image segmentation Pixel Statistical analysis image coding Testing Filters Meteorology Europe Africa Soil

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COST292 experimental framework for TRECVID 2006

COST292 experimental framework for TRECVID 2006

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TREC Video Retrieval Evaluation, TRECVID 2006

作者： Ćalić, J. Krämer, P. Naci, U. Vrochidis, S. Aksoy, S. Zhangk, Q. Benois-Pineau, J. Saracoglu, A. Doulaverakis, C. Jarina, R. Campbell, N. Mezaris, V. Kompatsiaris, I. Spyrou, E. Koumoulos, G. Avrithis, Y. Dalkilic, A. Alatan, A. Hanjalic, A. Izquierdo, E. Dept. of Computer Science University of Bristol 2.11 MVB Woodland Road Bristol BS8 1UB United Kingdom LaBRI University of Bordeaux 1 351 cours de la Libération F-33405 Talence France Delft University of Technology Mekelweg 4 2628CD Delft Netherlands Informatics and Telematics Institute Centre for Research and Technology Hellas Thermi-Panorama Road P.O. Box 361 57001 Thermi-Thessaloniki Greece Department of Computer Engineering Bilkent University Bilkent 06800 Ankara Turkey Department of Electronic Engineering Queen Mary University of London Mile End London E1 4NS United Kingdom Department Of Electrical and Electronics Engineering Middle East Technical University 06531 Ankara Turkey Image Video and Multimedia Laboratory National Technical University of Athens 9 Iroon Polytechniou Str 157 80 Athens Greece Department of Computer Engineering Hacettepe University Cankaya 06532 Ankara Turkey Department of Telecommunications University of Zilina Univerzitna 1 010 26 Zilina Slovakia

In this paper we give an overview of the four TRECVID tasks submitted by COST292, European network of institutions in the area of semantic multimodal analysis and retrieval of digital video media. Initially, we present shot boundary evaluation method based on results merged using a confidence measure. The two SB detectors user here are presented, one of the Technical University of Delft and one of the LaBRI, University of Bordeaux 1, followed by the description of the merging algorithm. The high-level feature extraction task comprises three separate systems. The first system, developed by the National Technical University of Athens (NTUA) utilises a set of MPEG-7 low-level descriptors and Latent Semantic Analysis to detect the features. The second system, developed by Bilkent University, uses a Bayesian classifier trained with a "bag of subregions" for each keyframe. The third system by the Middle East Technical University (METU) exploits textual information in the video using character recognition methodology. The system submitted to the search task is an interactive retrieval application developed by Queen Mary, University of London, University of Zilina and ITI from Thessaloniki, combining basic retrieval functionalities in various modalities (i.e. visual, audio, textual) with a user interface supporting the submission of queries using any combination of the available retrieval tools and the accumulation of relevant retrieval results over all queries submitted by a single user during a specified time interval. Finally, the rushes task submission comprises a video summarisation and browsing system specifically designed to intuitively and efficiently presents rushes material in video production environment. This system is a result of joint work of University of Bristol, Technical University of Delft and LaBRI, University of Bordeaux 1.

关键词： Semantics

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Medical Data Mining using Particle Swarm Optimization for Temporal Lobe Epilepsy

Medical Data Mining using Particle Swarm Optimization for Te...

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Congress on Evolutionary Computation

作者： M. Ghannad-Rezaie H. Soltanain-Zadeh M.-R. Siadat K.V. Elisevich Henry Ford Health System and Wayne State University Detroit MI USA Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Neurosurgery Department Henry Ford Health System Detroit MI USA

In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians and decrease decision accuracy. computerized knowledge extraction is an active area of research in medical informatics. This paper suggests a new medical data mining approach using an advanced swarm intelligence data mining algorithm. Considering medical knowledge discovery difficulties, this approach addresses common issues such as missing value management and interactive rule extraction. Here, surgery candidate selection in temporal lobe epilepsy is the main target application. However, the general idea can be applied to other medical knowledge discovery problems. Experimental results show noticeable performance improvement in the final rule-set quality while the method is flexible and fast.

关键词： Data mining Particle swarm optimization Temporal lobe Epilepsy Medical diagnostic imaging Biomedical imaging Coronary arteriosclerosis Diseases Surgery Medical services

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Color reduction by using a new self-growing and self-organized neural network

Color reduction by using a new self-growing and self-organiz...

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2nd International Conference on Video, Vision and Graphics, VVG 2005

作者： Atsalakis, A. Papamarkos, N. Image Processing and Multimedia Laboratory Department of Electrical and Computer Engineering Democritus University of Thrace 67100 Xanthi Greece

ISBN: (纸本)9783905673579

A new method for the reduction of the number of colors in a digital image is proposed. The new method is based on the developed of a new neural network classifier that combines the advantages of the Growing Neural Gas (GNG) and the Kohonen Self-Organized Feature Map (SOFM) neural networks. We call the new neural network: Self-Growing and Self-Organized Neural Gas (SGONG). Its main advantage is that it defines the number of the created neurons and their topology in an automatic way. As a consecutive, isolated color classes, which may correspond to significant image details, can be obtained. The SGONG is fed by the color components and additional spatial features. To speed up the entire algorithm and to reduce memory requirements, a fractal scanning sub-sampling technique is used. The method is applicable to any type of color images and it can accommodate any type of color space. © The Eurographics Association 2005.

关键词： Color

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Brain MR image segmentation using tabu search and hidden markov random field model

Brain MR image segmentation using tabu search and hidden mar...

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2nd Indian International Conference on Artificial Intelligence, IICAI 2005

作者： Nanda, P.K. Patra, D. Pradhan, A. Department of Electrical Engineering Image Processing and Computer Vision Laboratory National Institute of Technology Rourkela Orissa 769008 India

ISBN: (纸本)0972741216

In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Field (GHMRF) is used to model the available degraded image. In supervised framework, the apriori image MRF model parameters as well as the GHMRF model parameters are assumed to be known. The class labels are estimated using the Maximum a Posteriori (MAP) estimation criterion. In unsupervised framework, the problem of model parameter estimation and label estimation is formulated in Expectation Maximization (EM) framework. The labels are estimated using the proposed Tabu Search algorithm while the model parameters are the maximum likelihood estimates. Our proposed algorithm yields results with arbitrary initial paramater set and thus overcomes the problem of proper choice of initial parameters. The results obtained are comparable with the results obtained by using the algorithm proposed by Zhang ***. [15] , where the Iterated Conditional Mode (ICJM) algorithm is used for computing the MAP estimates. Copyright © IICAI 2005.

关键词： Tabu search

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Face recognition through mismatch driven representations of the face

Face recognition through mismatch driven representations of ...

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2nd Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS

作者： Lucey, Simon Chen, Tsuhan Advanced Multimedia Processing Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 United States

ISBN: (纸本)0780394240

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. ©2005 IEEE.

关键词： Face recognition

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Using overlapping distributions to deal with face pose mismatch

Using overlapping distributions to deal with face pose misma...

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2005 16th British Machine Vision Conference, BMVC 2005

作者： Lucey, Simon Chen, Tsuhan Advanced Multimedia Processing Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 United States

ISBN: (纸本)1901725294

Representing the face as a distribution of freely moving patches, which we refer to as a "free-parts" representation, has recently demonstrated some benefit in the task of face verification. This benefit can be largely attributed to the representation's natural ability to deal with local appearance variation within the face. Hitherto, a major limitation that has hindered the wider adoption of this type of facial representation, for the task of face verification, has been its poor ability to take advantage of prior knowledge concerning mismatches in context;such as pose. This paper goes some way to alleviating these limitations by making two novel contributions: (i) Demonstrating that free-parts distributions of a client's face for different poses overlap to such a degree that a considerable amount of discrimination is preserved in the intersection. (ii) Through the off-line estimation of subject-independent pose dependent priors, an alternative to the canonical log-likelihood measure can be employed that takes advantage of this intersection and is less sensitive to mismatch in the presence of pose variation.

关键词： Face recognition

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Three-dimensional optical remote sensing using optical scanning holography

Three-dimensional optical remote sensing using optical scann...

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Current Research on image processing for 3D Information Displays

作者： Poon, Ting-Chung Optical Image Processing Laboratory Bradley Department of Electrical and Computer Engineering Virginia Tech. Blacksburg VA 24061 United States

No abstract available

ISBN: (纸本)0819458066

No abstract available

关键词： optical heterodyning depth detection optical scanning holography optical remote sensing optical remote sensing Optical scanning Optical heterodyning Holography Targets

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