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International Conference on Systems and Informatics

作者： Guoqing Cui Jie Yang Masoumeh Zareapoor Jiechen Wang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Complex Network and Control Lab Shanghai Jiao Tong University

ISBN: (纸本)9781509055227

Feature selection, as a preprocessing step to machine learning, plays a pivotal role in removing irrelevant data, reducing dimensionality and improving performance evaluations. Recent years, sparse representation has become a useful tool for both supervised and unsupervised feature selection. So far, most of these algorithms still have many problems such as large computation load, performance with poor stability. Thus, this paper proposes a new unsupervised feature selection algorithm via sparse representation (UFSSR), with respect to efficiency and effectiveness. Firstly, this paper reconstructs part of data matrix via sparse representation, which makes the proposed algorithm be robust and independent of domain knowledge. Then, to reduce the reconstruction error, a new feature evaluation function is given to rank all features. Theoretical analysis and experiments compared with many popular algorithms on a set of datasets demonstrate the improvements brought by UFSSR.

关键词： Unsupervised feature selection Sparse representation Feature evaluation function Computation load Stability

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An image fusion method of multi-scale image based on HMM and genetic algorithms

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Journal of Computational Information Systems 2015年第12期11卷 4367-4374页

作者： Jiang, Zetao Wu, Donghui The Institute of Computer Science and Engineering Guilin University of Electronic Technology Guilin China The Key Lab of Image Processing and Pattern Recognition of Jiangxi Province Nanchang Hangkong University Nanchang China

At present, in the field of pixel-level image fusion, researchers tend to treat each pixel independently, which destroys the relationship between the images to be fused. In view of this defects, this paper aims to propose a method for multi-scale image fusion based on Genetic Algorithm (GA) under the guidance of Hidden Markov Model (HMM). This fusion method is set on the following principles. First of all, the wavelet transformation (WT) of the two images to be fused will be conducted. And then establish HMM for the fusion coefficients from high to low in descending hierarchical order. Finally, guided by HMM, the author applies GA to searching hierarchically for the optimal fusion coefficient. With this method, the best fusion effect will be achieved. This method take good advantage of the correlation information between the images to be fused so as to improve the fidelity and accuracy of the fusion. Given this, the author makes an empirical analysis on this fusion method, which proves to be feasible and effective. ©, 2015, Binary Information Press. All right reserved.

关键词： Genetic algorithms

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Binary pattern flavored feature extractors for Facial Expression recognition: An overview

Binary pattern flavored feature extractors for Facial Expres...

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Proceedings of the International Convention MIPRO

作者： Rasmus Lyngby Kristensen Zheng-Hua Tan Zhanyu Ma Jun Guo Section of Image Analysis and Computer Graphics Technical University of Denmark Kgs. Lyngby Denmark Signal and Information Processing section (SIP) Aalborg University Aalborg Denmark Pattern Recognition and Intelligent System Lab. Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781479981748

This paper conducts a survey of modern binary pattern flavored feature extractors applied to the Facial Expression recognition (FER) problem. In total, 26 different feature extractors are included, of which six are selected for in depth description. In addition, the paper unifies important FER terminology, describes open challenges, and provides recommendations to scientific evaluation of FER systems. Lastly, it studies the facial expression recognition accuracy and blur invariance of the Local Frequency Descriptor. The paper seeks to bring together disjointed studies, and the main contribution is to provide a solid overview for future research.

关键词： Feature extraction Face Face recognition Databases Three-dimensional displays Accuracy Gold

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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...

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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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SAR image CLASSIFICATION WITH NORMALIZED GAMMA PROCESS MIXTURES

SAR IMAGE CLASSIFICATION WITH NORMALIZED GAMMA PROCESS MIXTU...

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IEEE International Conference on image processing

作者： Koray Kayabol Bilge Gunsel Multimedia Signal Processing and Pattern Recognition Lab. Istanbul Technical University

ISBN: (纸本)9781479923427

We propose a novel image prior for the non-parametric Bayesian mixture model based unsupervised classification of SAR images. We modified the Normalized Gamma Process prior that constitutes a more general form of the Dirichlet Process prior in order to enclose the contribution of the adjacent pixels into the classification scheme. This yields an image classification prior embedded in a mixture model that allows infinite number of clusters and enables reaching to smoothed classification maps. Based on the classification results obtained on synthetic and real TerraSAR-X images, it is shown that the proposed model is capable of accurately classifying the pixels. It applies a simple iterative update scheme at a single run without performing a hierarchical clustering strategy as used in the previously proposed methods. It is also demonstrated that the model order estimation accuracy of the proposed method outperforms the conventional finite mixture models.

关键词： Infinite mixture models Normalized gamma process mixtures Nonparametric Bayesian image classification SAR images image classification Mixture models images Radar polarimetry classification scheme pixel Rescue Synthetic aperture radar Specific absorption rate SAFETY ANALYSIS REPORTS mixtures

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The design of multi-channel signals source with high-speed and high-precision based on FPGA

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Sensors and Transducers 2013年第SPEC.ISS.5期21卷 164-168页

作者： Du, Xiao-Dan Hu, Qing Yan, Tao Liu, Yong-Hong College of Information Science and Technology of Chengdu University Sichuan Chengdu 610106 China College of Electronic and Information Engineering of Chengdu University Sichuan Chengdu 610106 China Key Lab. in Colleges for Pattern Recognition and Intelligent Infor. Processing of Sichuan Province Sichuan Chengdu 610106 China

The multi-channel signals source that the structure is simple and flexible control is proposed in the article, with FPGA and high-speed D/A as its core. The choice of parts of apparatus, hardware constitution and design of software of the signals source are recommended here. Before the hardware designed, detailed theoretical analyses and quantitative description for the key factors on effecting the precision of signal source are given, and when debugging in hardware circuit is completed, on the base of analysis, errors estimation were verified with experimental results. It has provided high-precision signal related to the static and dynamic characteristics test accuracy of measured system for encoder and memory. By experiment and application it can meet the system requirements and has some theoretic and practical value. © 2013 IFSA.

关键词： Field programmable gate arrays (FPGA)

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Classification of gothic and baroque architectural elements

Classification of gothic and baroque architectural elements

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2012 19th International Conference on Systems, Signals and image processing, IWSSIP 2012

作者： Shalunts, Gayane Haxhimusa, Yll Sablatnig, Robert Institute of Computer Aided Automation Computer Vision Lab. Vienna University of Technology Austria Institute of Computer Graphics and Algorithms Pattern Recognition and Image Processing Lab. Vienna University of Technology Austria

ISBN: (纸本)9783200023284

Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectural styles is viewed as a task of classifying separate architectural structural elements. In the scope of building facade architectural style classification the current paper targets the problem of classification of Gothic and Baroque architectural elements called tracery, pediment and balustrade. Since certain gradient directions dominate on the shape of each architectural element, discrimination between dominating gradients means classification of architectural elements and thus architectural styles. We use local features to describe gradient directions. Our approach is based on clustering and learning of local features and yields a high classification rate. © 2012 Institute of Telecommunica.

关键词： Classification (of information)

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Segmentation of building facade domes

Segmentation of building facade domes

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17th Iberoamerican Congress on Progress in pattern recognition, image Analysis, Computer Vision, and Applications, CIARP 2012

作者： Shalunts, Gayane Haxhimusa, Yll Sablatnig, Robert Vienna University of Technology Computer Vision Lab. Austria Vienna University of Technology Pattern Recongition and Image Processing Lab. Austria

ISBN: (纸本)9783642332746

Domes are architectural structural elements typical for ecclesiastical and secular grand buildings, like churches, mosques, palaces, capitols and city halls. The current paper targets the problem of segmentation of domes within the framework of architectural style classification of building facades. We perform segmentation of building facade domes by combining bilateral symmetry detection, graph-based segmentation approaches and image analysis and processing technics into a single method. Our algorithm achieves good segmentation results on buildings belonging to variety of architectural styles, such as Renaissanse, Neo-Renaissance, Baroque, Neo-Baroque, Neoclassical and Islamic. © 2012 Springer-Verlag.

关键词： Domes

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Feedback-free and hybrid distributed video coding using neural networks

Feedback-free and hybrid distributed video coding using neur...

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2012 11th International Conference on Information Science, Signal processing and their Applications, ISSPA 2012

作者： Nickaein, Isaac Rahmati, Mohammad Ghidary, Saeed Shiry Zohrabi, Abtin Image Processing and Pattern Recognition Lab Department of Computer Engineering and IT Amirkabir University of Technology Tehran Iran Abtin Zohrabi Faculty of Computer Science University of New Brunswick Canada

ISBN: (纸本)9781467303828

Distributed Video Coding (DVC) is a new class of video coding techniques with the aim of coding the decentralized video sources. While the Stanford Wyner-Ziv codec is a well-known architecture in DVC literature, one of its main drawbacks is the presence of a feedback channel from the decoder to the encoder. This feedback channel makes the use of the codec impractical in some applications. Since the only application of the feedback channel is in requesting more parity bits from the encoder, it could be omitted if the encoder estimates the required parity bits and sends them at once. In this paper, a new method of bitrate estimation using a neural network trained by a new set of features is proposed. In addition, a Hybrid mode is proposed that reduces computational complexity at the decoder in a conventional Wyner-Ziv codec. © 2012 IEEE.

关键词： image coding

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Feedback-free and hybrid distributed video coding using neural networks

Feedback-free and hybrid distributed video coding using neur...

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International Symposium on Signal processing and Its Applications (ISSPA)

作者： Isaac Nickaein Mohammad Rahmati Saeed Shiry Ghidary Abtin Zohrabi Image Processing and Pattern Recognition Lab Amirkabir University of Technology Tehran Iran Abtin Zohrabi University of New Brunswick Canada

关键词： Bit rate Decoding Encoding Estimation Video coding Neural networks Video sequences

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