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Robust audio watermark decoding by nonlinear classification

Robust audio watermark decoding by nonlinear classification

引用

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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Multiscale Deep Convolutional Networks for Characterization and Detection of Alzheimer's Disease Using MR images 26

Multiscale Deep Convolutional Networks for Characterization ...

引用

26th IEEE International Conference on image processing, ICIP 2019

作者： Ge, Chenjie Qu, Qixun Gu, Irene Yu-Hua Store Jakola, Asgeir Dept. of Electrical Engineering Chalmers University of Technology Sweden Inst. of Neuroscience and Physiology Sahlgrenska Academy University of Gothenburg Sweden Inst. of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)9781538662496

This paper addresses the issues of Alzheimer's disease (AD) characterization and detection from Magnetic Resonance images (MRIs). Many existing AD detection methods use single-scale feature learning from brain scans. In this paper, we propose a multiscale deep learning architecture for learning AD features. The main contributions of the paper include: (a) propose a novel 3D multiscale CNN architecture for the dedicated task of AD detection;(b) propose a feature fusion and enhancement strategy for multiscale features;(c) empirical study on the impact of several settings, including two dataset partitioning approaches, and the use of multiscale and feature enhancement. Experiments were conducted on an open ADNI dataset (1198 brain scans from 337 subjects), test results have shown the effectiveness of the proposed method with test accuracy of 93.53%, 87.24% (best, average) on subject-separated dataset, and 99.44%, 98.80% (best, average) on random brain scan-partitioned dataset. Comparison with eight existing methods has provided further support to the proposed method. © 2019 IEEE.

关键词： Feature extraction Three-dimensional displays Training Alzheimer's disease Magnetic resonance imaging Testing

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Application constraints in the design of an automatic reading device for analog display instruments

Application constraints in the design of an automatic readin...

引用

IEEE Workshop on Applications of Computer Vision (WACV)

作者： R. Sablatnig W.G. Kropatsch Dept. of Pattern Recognition & Image Process. Wien Univ. Austria Institute for Automations Department of Pattern Recognition and Image Processing Technical University of of Vienna Vienna Austria

An analysis system design based on experience with a successful application in the field of inspection and calibration of an analog display measuring instrument is presented in this paper. First the measuring instrument is divided into its primitiva, defining the a priori known parameter of the primitiva: shape, relative position and size. According to the shape of the primitiva pattern recognition algorithms are used to detect the primitiva in intensity images. These independent detection algorithms are then grouped into a detecting order with respect to efficiency. Following a discussion of the general design of the detecting algorithm, specific constraints of the application and the industrial environment are considered in order to refine the general design to an applicable and efficient device by modifying both hardware and software configuration depending on the given constraints. Finally, results of the implementation of the algorithm and the constructed image acquisition device are discussed.< >

关键词： Instruments Shape measurement Algorithm design and analysis System analysis and design Inspection Calibration Displays Position measurement Size measurement pattern recognition

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Human activity recognition in images using SVMs and geodesics on smooth manifolds 14

Human activity recognition in images using SVMs and geodesic...

引用

8th ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2014

作者： Yun, Yixiao Fu, Keren Gu, Irene Yu-Hua Aghajan, Hamid Yang, Jie Dept. of Signals and Systems Chalmers University of Technology Sweden Inst. of Image Processing and Pattern Recognition Shanghai Jiao Tong University China IMinds Ghent University Belgium AIR Lab. Stanford University United States

ISBN: (纸本)9781450329255

This paper addresses the problem of human activity recognition in still images. We propose a novel method that focuses on human-object interaction for feature representation of activities on Riemannian manifolds, and exploits underlying Riemannian geometry for classification. The main contributions of the paper include: (a) represent human activity by appearance features from local patches centered at hands containing interacting objects, and by structural features formed from the detected human skeleton containing the head, torso axis and hands;(b) formulate SVM kernel function based on geodesics on Riemannian manifolds under the log-Euclidean metric;(c) apply multi-class SVM classifier on the manifold under the one-against-all strategy. Experiments were conducted on a dataset containing 17196 images in 12 classes of activities from 4 subjects. Test results, evaluations, and comparisons with state-of-the-art methods provide support to the effectiveness of the proposed scheme. Copyright 2014 ACM.

关键词： Support vector machines

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Incremental non-negative matrix factorization for dynamic background modelling

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

引用

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 comparision of Model-based methods for knee cartilage segmentation

A comparision of Model-based methods for knee cartilage segm...

引用

2nd International Conference on Computer Vision Theory and Applications, VISAPP 2007

作者： Cheong, J. Faggian, N. Langs, G. Suter, D. Cicuttini, F. Dept. of Electrical Dept. of Computer Systems Engineering Monash University Australia Clayton School of Information Technology Monash University Australia Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria Dept. of Epidemiology Dept. of Preventive Medicine Monash University Australia

Osteoarthritis is a chronic and crippling disease affecting an increasing number of people each year. With no known cure, it is expected to reach epidemic proportions in the near future. Accurate segmentation of knee cartilage from magnetic resonance imaging (MRI) scans facilitates the measurement of cartilage volume present in a patient's knee, thus enabling medical clinicians to detect the onset of osteoarthritis and also crucially, to study its effects. This paper compares four model-based segmentation methods popular for medical data segmentation, namely Active Shape Models (ASM) (Cootes et al., 1995), Active Appearance Models (AAM) (Cootes et al., 2001), Patch-based Active Appearance Models (PAAM) (Faggian et al., 2006), and Active Feature Models (AFM) (Langs et al., 2006). A comprehensive analysis of how accurately these methods segment human tibial cartilage is presented. The results obtained were benchmarked against the current "gold standard" (cartilage segmented manually by trained clinicians) and indicate that modeling local texture features around each landmark provides the best results for segmenting human tibial cartilage.

关键词： Medical imaging

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Indefinite kernel spectral learning 30

Indefinite kernel spectral learning

引用

30th Benelux Conference on Artificial Intelligence, BNAIC 2018

作者： Mehrkanoon, Siamak Huang, Xiaolin Suykens, Johan A.K. Dept. of Data Science and Knowledge Engineering Maastricht University Netherlands Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200240 China KU Leuven ESAT-STADIUS Kasteelpark Arenberg 10 LeuvenB-3001 Belgium

This paper introduces the indefinite learning in the framework of least squares support vector machines (LS-SVM). Here the analysis of the Multi-Class Semi-Supervised Kernel Spectral Clustering (MSS-KSC) model with indefinite kernels is provided. In indefinite MSS-KSC one finds the solution by solving a linear system of equations in the dual. In addition the use of the propped indefinite model for large scale data using Nyström approximation technique as well as unsupervised learning using Kernel Spectral Clustering are also discussed in the published full paper1. Experimental results on several real-life datasets are given to illustrate the efficiency of the proposed indefinite kernel spectral learning. © 2018 University of Groningen. All rights reserved.

关键词： Clustering algorithms

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Visual Tracking via Nonnegative Regularization Multiple Locality Coding

Visual Tracking via Nonnegative Regularization Multiple Loca...

引用

International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Fanghui Liu Tao Zhou Jie Yang Irene Y. H. Gu Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Dept. of Signals and Systems Chalmers University of Technology

ISBN: (纸本)9781467397124

This paper presents a novel object tracking method based on approximated Locality-constrained Linear Coding (LLC). Rather than using a non-negativity constraint on encoding coefficients to guarantee these elements nonnegative, in this paper, the non-negativity constraint is substituted for a conventional l2 norm regularization term in approximated LLC to obtain the similar nonnegative effect. And we provide a detailed and adequate explanation in theoretical analysis to clarify the rationality of this replacement. Instead of specifying fixed K nearest neighbors to construct the local dictionary, a series of different dictionaries with pre-defined numbers of nearest neighbors are selected. Weights of these various dictionaries are also learned from approximated LLC in the similar framework. In order to alleviate tracking drifts, we propose a simple and efficient occlusion detection method. The occlusion detection criterion mainly depends on whether negative templates are selected to represent the severe occluded target. Both qualitative and quantitative evaluations on several challenging sequences show that the proposed tracking algorithm achieves favorable performance compared with other state-of-the-art methods.

关键词： Dictionaries Encoding Target tracking Visualization Bismuth image reconstruction image coding

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A Modified Numerical Integration Method for Deformable Object Animation

A Modified Numerical Integration Method for Deformable Objec...

引用

Asia Simulation Conference 2007, AsiaSim 2007

作者： Hu, Xinrong Wei, Lan Li, Dehua Dept. of Computer Science and Technology WuHan University of Science and Engineering WuHan 430074 China Institute for Pattern Recognition and Artificial Intelligence State Education Commission Laboratory for Image Processing and Intelligence Control HuaZhong Univ. of Science and Technology WuHan 430074 China

ISBN: (纸本)9783540775997

A satisfied deformable object simulation should be general, accurate, efficient and stable. Explicit, implicit and semi-implicit numerical integration methods have contributed to large performance enhancements in the field of deformable simulation. Cloth is the most representative deformable object. In this paper, we propose an improved embedded Runge-Kutta integration method to solve the deformable simulation that based on classical spring-mass model. Traditional embedded Runge-Kutta methods generally solve ordinary differential equations of deformable object simulation. Most of them tend to concentrate on the efficiency of the simulation process, and not the fidelity of the simulation result. We investigate and determine the extent to which the overall quality must be compromised in order for the stable conditions to be satisfied. The improved Runge-Kutta method proposed in our paper incorporates the fixed time step and adaptive time step in solving cloth motion equations to achieve a controllable error evaluation. Compared with the other Runge-Kutta methods, the proposed method has some advantages for cloth simulation: controllable error evaluation without extra computations, excellent efficiency, good stability and satisfied precision. Experiment demonstrates that this method results in simulation efficiency improvements and is considerable practicable. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Animation

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Survey on Monocular dept. Estimation for Unmanned Aerial Vehicles using Deep Learning

Survey on Monocular Depth Estimation for Unmanned Aerial Veh...

引用

IEEE International Conference on Intelligent Computer Communication and processing (ICCP)

作者： Horatiu Florea Sergiu Nedevschi Computer Science Dept. Image Processing and Pattern Recognition Research Center Technical University of Cluj-Napoca Cluj-Napoca Romania

ISBN: (纸本)9781665464383

Deep learning-based solutions for the ill-posed problem of Monocular dept. Estimation (MDE) from 2D color images have shown potential in recent years, spurring a very active field of research. Most state-of-the-art proposals focus on solving the problem in the context of automotive advanced driver assistance and/or autonomous driving systems. While presenting their own complexities and challenges, the vast majority of road environments exhibit a number of commonalities amongst themselves. The aerial domain in which modern Unmanned Aerial Vehicles (UAVs) operate is significantly different and features a large variety of possible scenes based on the specific mission carried out. The increasing number of applications for UAVs could benefit from more advanced learning-based MDE solutions for recovering 3D geometric information from the scene. In this paper, we conduct a study of existing research on the topic of MDE specifically tailored for aerial views, as well as presenting the datasets and tools currently supporting such research, high-lighting the challenges that remain. To the best of our knowledge, this is the first survey covering this field.

关键词： Deep learning Technological innovation Three-dimensional displays Roads Estimation Autonomous aerial vehicles Complexity theory

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