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作者： Ulker, Yener Gunsel, Bilge Kirbiz, Serap Multimedia Signal Processing and Pattern Recognition Lab. Istanbul Technical University Dep. of Electronics and Communications Engineering 34469 Maslak Istanbul Turkey

ISBN: (纸本)9781424421756

In contrast to the fixed rate modeling of the conventional methods, recently introduced variable rate particle filters (VRPF) achieves to track maneuvering objects with a small number of states by imposing a probability distribution on state arrival times. Although this enables VRPF an appealing method, representing the target motion dynamics with a single model hinders the capability of estimating maneuver parameters precisely. To overcome this weakness we have incorporated multiple model approach with the variable rate model structure. The introduced model referred as Multiple Model Variable Rate Particle Filter (MM-VRPF) utilizes a parsimonious representation for smooth regions of trajectory while it adaptively locates frequent state points at high maneuver regions, resulting in a much more accurate tracking. Simulation results obtained in a bearings-only target tracking problem show that the proposed model outperforms the conventional VRPF, the fixed rate multiple model particle filters (MMPF) and interacting multiple model using extended Kalman filters (IMM-EKF). © 2008 IEEE.

关键词： Extended Kalman filters

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Incremental non-negative matrix factorization for dynamic background modelling

Incremental non-negative matrix factorization for dynamic ba...

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7th International Workshop on pattern recognition in Information Systems PRIS 2007;In Conjunction with ICEIS 2007

作者： Bucak, Serhat S. Gunsel, Bilge Gursoy, Ozan Multimedia Signal Processing and Pattern Recognition Lab. Dept. of Electronics and Comm. Eng. Istanbul Technical University 34469 Maslak Istanbul Turkey

ISBN: (纸本)9789728865931

In this paper, an incremental algorithm which is derived from Non-negative Matrix Factorization (NMF) is proposed for background modeling in surveillance type of video sequences. The adopted algorithm, which is called as Incremental NMF (INMF), is capable of modeling dynamic content of the surveillance video and controlling contribution of the subsequent observations to the existing representation properly. INMF preserves additive, parts-based representation, and dimension reduction capability of NMF without increasing the computational load. Test results are reported to compare background modeling performances of batch-mode and incremental NMF in surveillance type of video. Moreover, test results obtained by the incremental PCA are also given for comparison purposes. It is shown that INMF outperforms the conventional batch-mode NMF in all aspects of dynamic background modeling. Although object tracking performance of INMF and the incremental PCA are comparable, INMF is much more robust to illumination changes.

关键词： Non-negative matrix factorization

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A boosting discriminative model for moving cast shadow detection

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6th International Conference on Energy Minimization Methods in Computer Vision and pattern recognition, EMMCVPR 2007

作者： Yufei, Zha Ying, Chu Duyan, Bi Signal and Information Processing Lab. Engineering College of Air Force Engineering University xi'an China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

ISBN: (纸本)9783540741954

Moving cast shadow causes serious problem while segmenting and extracting foreground from image sequences, due to the misclassification of moving shadow as foreground. This paper proposes a boosting discriminative model for moving cast shadow detection. Firstly, color invariance subspace and texture invariance subspace are obtained by the color and texture difference between current image and background image;then, boosting is selected based on theses subspaces to discriminate cast shadow from moving objects;finally, temporal and spatial coherence of shadow and foreground is employed on Discriminative Random Fields for accurate image segmentation through graph cut. Results show that the proposed method excels classical method both in indoor and outdoor scene. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Image analysis

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Robust audio watermark decoding by nonlinear classification

Robust audio watermark decoding by nonlinear classification

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13th European signal processing Conference, EUSIPCO 2005

作者： Kirbiz, S. Yaslan, Y. Günsel, B. Multimedia Signal Processing and Pattern Recognition Lab. Dept. of Electronics and Communications Eng. Istanbul Technical University 34469 Istanbul Turkey

ISBN: (纸本)1604238216

This paper introduces an audio watermark (WM) decoding scheme that performs a Support Vector Machine (SVM) based supervised learning followed by a blind decoding. The decoding process is modelled as a two-class classification procedure. Initially, wavelet decomposition is performed on the training audio signals, and the decomposed audio frames watermarked with +1 and -1 constitute the training sets for Class 1 and Class 2, respectively. The developed system enables to extract embedded WM data at lower than -40dB Watermark-to-signal- Ratio (WSR) levels with more than 95% accuracy and it is robust to degradations including audio compression (MP3, AAC), and additive noise. It is shown that the proposed audio WM decoder eliminates the drawbacks of correlation-based methods.

关键词： Additive noise

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Content-based access to art paintings

Content-based access to art paintings

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IEEE International Conference on Image processing

作者： B. Gunsel S. Sariel O. Icoglu Multimedia Signal Processing and Pattern Recognition Lab Electrical-Electronics Engineering Faculty Istanbul Technical University Istanbul Turkey

This paper introduces ArtHistorian, a content-based classification and indexing system that represents the visual content of art paintings by a six-dimensional feature set. The introduced feature set is robust to scale changes and can handle variations in lighting conditions. A nonlinear SVM classifier included in the system learns the characteristics of fundamental art movements and painting styles. A hybrid classifier that combines PCA representation of paintings with the SVM classification is also exploited. It is shown that ArtHistorian is capable of classifying art paintings based on painters as well as art movements with an accuracy of greater than 90% and its false alarm ratio is very small. The developed system enables the user to run content-based queries and to retrieve from painting databases created in XML format.

关键词： Art Painting Support vector machines Support vector machine classification Indexing Robustness Principal component analysis Information retrieval Content based retrieval Databases

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Classification and indexing of paintings based on art movements 12

Classification and indexing of paintings based on art moveme...

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12th European signal processing Conference, EUSIPCO 2004

作者： Icoglu, Oguz Gunsel, Bilge Sariel, Sanem Multimedia Signal Processing and Pattern Recognition Lab. Electrical-Electronics Eng. Faculty Istanbul Technical University Maslak-Istanbul34469 Turkey Vienna University of Technology Building Physics and Human Ecology Institute Austria

ISBN: (纸本)9783200001657

This paper outlines the automatic extraction of features of paintings' art movements such as classicism, impressionism and cubism;and introduces a system developed for the classification and indexing of paintings based on their art movements. A six dimensional feature set is proposed for the representation of content and it is shown that the feature set enables to highlight art movements efficiently. In the classifier design, statistical pattern recognition approach is exploited and Bayesian, k-NN and SVM classifiers are employed. A classification accuracy of over 90% is achieved with very small false alarm ratios while the lowest performance is obtained by the k-NN. System also offers a quick query based database search by indexing the paintings with their six dimensional feature vectors, and provides an applicable program for museums and exhibition centres. © 2004 EUSIPCO.

关键词： Query processing

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An integrated decoding framework for audio watermark extraction

An integrated decoding framework for audio watermark extract...

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International Conference on pattern recognition

作者： Y. Yaslan B. Gunsel Multimedia Signal Processing and Pattern Recognition Lab Electrical-Electronics Faculty. Department of Electronics and Communications Engineering Istanbul Technical University Maslak Istanbul Turkey

This paper proposes a blind audio watermark extraction technique that allows performing watermark decoding while installing data synchronization. The proposed decoding algorithm employs correlation techniques supported by a wavelet denoising process, thus improves the decoding performance significantly. A data adaptive nonlinear MPEG Layer 1 Model 1 compatible watermark encoder is designed for watermark embedding. A channel encoder is also included into the system to take the advantage of error correction. The method does not require the original audio for decoding and it is robust to channel noise, filtering as well as stereo-to-mono conversions. It allows working at very low watermark-to-signal ratios thus preserves inaudibility.

关键词： Watermarking Data mining Noise reduction signal processing pattern recognition Noise robustness Communication channels Meteorological radar Iterative decoding signal processing algorithms

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A Region-Based Representation of Images in MARS

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Journal of VLSI signal processing Systems for signal, Image, and Video Technology 1998年第1-2期20卷 137-150页

作者： Servetto, Sergio D. Rui, Yong Ramchandran, Kannan Huang, Thomas S. Beckman Inst. Adv. Sci. and Technol. Univ. Illinois at Urbana-Champaign Urbana IL 61801 United States Universidad Nacional de La Plata Argentina Univ. Illinois at Urbana-Champaign United States Comp. Res. Adv. Applications Group IBM Argentina Argentina Image Formation and Processing Group Beckman Institute UIUC United States Department of Computer Science UNLP Argentina Dept. of Elec. and Comp. Engineering UIUC United States Multimedia Commun. Res. Department Bell Laboratories Murray Hill NJ United States Info. Sciences Research Department AT and T Labs. Florham Park NJ United States Department of Computer Science UIUC United States Southeast University China Tsinghua University China University of Illinois Urbana-Champaign IL United States Image Formation and Processing Group Beckman Inst. Advance Sci. Technol. UIUC United States Vis. Technol. Grp. of Microsoft Res. Redmond WA United States City College of New York United States Columbia University United States AT and T Bell Labs. United States Ctr. for Telecommunications Research Columbia University United States Elec. and Comp. Eng. Department United States Beckman Institute Coordinated Science Laboratory IL United States IEEE Signal Processing Society United States IEEE IMDSP Technical Committee United States IEEE Transactions on Image Proc. United States National Taiwan University Taipei Taiwan Massachusetts Inst. of Technology Cambridge MA United States Department of Electrical Engineering MIT United States School of Electrical Engineering United States Lab. for Info. and Signal Processing Purdue University United States Dept. of Elec. and Comp. Engineering United States Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Inst. Adv. Sci. and Technol. United States MIT Lincoln Laboratory IBM Thomas J. Watson Research Center Rheinishes Landes Museum Bonn Germany Swiss Institutes of Technology Zurich Switzerland Swiss Institutes of Technology Lausanne S

We study the problem of representing images within a multimedia Database Management System (DBMS), in order to support fast retrieval operations without compromising storage efficiency. To achieve this goal, we propose new image coding techniques which combine a wavelet representation, embedded coding of the wavelet coefficients, and segmentation of image-domain regions in the wavelet domain. A bitstream is generated in which each image region is encoded independently of other regions, without having to explicitly store information describing the regions. Simulation results show that our proposed algorithms achieve coding performance which compares favorably, both perceptually and objectively, to that achieved using state-of-the-art image/video coding techniques while additionally providing region-based support.

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multimedia Content Representation, Classification and Security 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Bilge Gunsel Anil K. Jain A. Murat Tekalp Bülent Sankur

ISBN: (数字)9783540393931

ISBN: (纸本)9783540393924

We would like to welcome you to the proceedings of MRCS 2006, Workshop on multimedia Content Representation, Classi?cation and Security, held Sept- ber 11–13, 2006, in Istanbul, Turkey. The goal of MRCS 2006 was to provide an erudite but friendly forum where academic and industrial researchers could interact, discuss emerging multimedia techniques and assess the signi?cance of content representation and security techniques within their problem domains. We received more than 190 submissions from 30 countries. All papers were subjected to thorough peer review. The ?nal decisions were based on the cri- cisms and recommendations of the reviewers and the relevance of papers to the goals of the conference. Only 52% of the papers submitted were accepted for inclusion in the program. In addition to the contributed papers, four distinguished researchers agreed to deliver keynote speeches, namely: – Ed Delp on multimedia security – Pierre Moulin on data hiding – John Smith on multimedia content-based indexing and search – Mar´ ?o A. T. Figueiredo on semi-supervised learning.

关键词： Computer Applications multimedia Information Systems Information Storage and Retrieval Computer Communication Networks Information Systems Applications (incl. Internet) Image processing and Computer Vision

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