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Welcome from CSNT 2013 general chairs

Proceedings - 2013 International Conference on Communication...

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Proceedings - 2013 international conference on Communication Systems and Network Technologies, CSNT 2013 2013年 xviii-xix页

作者： Tomar, Geetam Dixit, Manish Machine Intelligence Research Labs India MITS Gwalior India

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Person re-identification by local feature based on super pixel

Person re-identification by local feature based on super pix...

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19th international conference on Advances in Multimedia Modeling, MMM 2013

作者： Liu, Cheng Zhao, Zhicheng Multimedia Communication and Pattern Recognition Labs. Beijing China Beijing Key Laboratory of Network System and Network Culture Xitucheng Road No. 10 Haidian District Beijing China

ISBN: (纸本)9783642357244

In many multi-camera surveillance systems, there is a need to identify whether a captured person have emerged before over the network of cameras. This is the person re-identification problem. In this paper, we propose a novel re-identification method based on super pixel feature. Firstly, local C-SIFT features based on super pixel are extracted as visual words, and appearance details are used to describe detecting objects. Secondly, a TF-IDF vocabulary index tree is built to speed up person search. Finally, an image-retrieval way is adopted to implement person re-identification. Experimental results on ETHZ dataset show that our method is better than the approach proposed by Schwartz *** and two machine learning methods based on SVM and PCA. © Springer-Verlag 2013.

关键词： Object detection

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Adaptive Motion pattern Analysis for machine Vision Based Moving Detection from UAV Aerial Images

Adaptive Motion Pattern Analysis for Machine Vision Based Mo...

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3rd international Visual Informatics conference (IVIC)

作者： Saif, A. F. M. Saifuddin Prabuwono, Anton Satria Mahayuddin, Zainal Rasyid Univ Kebangsaan Malaysia Fac Informat Sci & Technol Bangi Malaysia

ISBN: (纸本)9783319029573;9783319029580

In order to detect moving object from UAV aerial images motion analysis has started to get attention in recent years where motion of the objects along with moving camera needs to be estimated and compensated by using detection algorithm. Moving object detection from UAV aerial images based on motion analysis involves modeling the pixel value changes over time. Moving object detection with moving cameras from UAV aerial images is still an unsolved issue due to not considering irregular motion of camera and improper estimation of noise, object motion changes and finally unfixed moving object direction. This paper presents a low complexity based motion analysis framework for moving object detection along with camera motion estimation by considering motion change of moving object and unfixed moving object direction. Based on the experimental results it is expected that proposed motion vector estimation performs well for both invariant motion and invariant moving object direction.

关键词： machine vision motion analysis moving object detection

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A New SAFR Tool for Face recognition Using EGV-LBP-CMI-LDA Wrapped with Secured DWT Based Steganography

A New SAFR Tool for Face Recognition Using EGV-LBP-CMI-LDA W...

引用

IEEE international Advance Computing conference

作者： Shami Jhodge Girija Chiddarwar Gitanjali Shinde Department of MCA Sinhgad College of Management Department of Computer Engineering Sinhgad College of Engineering Department of Computer Engineering SKN College of Engineering

ISBN: (纸本)9781467345279

Face recognition technique nowadays is emerging as the most significant and challenging aspects in terms of security for identification of images in various fields viz. banking, police records, biometric etc. other than an individual's thumb and documented identification proofs. Till date for efficient net banking to be initiated, one has to provide the appropriate user name and password for purpose of authentication. This project introduces a vehicle to take a step forward in easy and more reliable authentication of an individual by providing Face Image along with User Name and Password to the system. In this an individual's face is identified by biometric authentication support with which, only a person whose account is, can access it. However while transferring this sensitive data of user image, from client machine to bank server it has to be protected from hackers and intruders from manhandling it, hence it is transferred using covert communication called Wavelet Decomposition based steganography. As face images are affected by different expressions, poses, occlusions, illuminations and aging over a period of time and it differs from the same person than those from different ones is the main difficult task in face recognition. Whenever image information is jointly co-ordinated in three aspects viz. image space, scale and orientation domains they carry much higher clues than seen in each domain individually. In the proposed method combination of Local Binary pattern (LBP) and Gabor features are used to increase the face recognition performance significantly to compare individual's face presentations. Hence face recognition and representation of Gabor faces are done using E-GV-LBP and CMI-LDA based feature recognition method. Gabor faces uses space, scale and orientation to support accurate face recognition, making net banking easier, authentic, reliable and user friendly.

关键词： DWT (Discrete Wavelet Transformation) E-GV-LBP (Effective Gabor Volume Linear Binary pattern) CMI (Conditional Mutual Information)

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Sparse representations of clustered video shots for action recognition

Sparse representations of clustered video shots for action r...

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international conference on Computer Science and Network Technology (ICCSNT)

作者： Yi Ding Hongtao Lu Department of Computer Science and Engineering Shanghai Jiao Tong University

ISBN: (纸本)9781479905607

In most action recognition tasks, the target videos are of different temporal length and an action may be repeated several times in one video. As a result, encoding the distribution of video feature points that are far away from each other or are detected from different occurrences of the action into the video representation is inappropriate. It is better that sub video shots containing different occurrences of the action are detected and encoded respectively. In this paper, a novel video representation framework in which video shots are detected efficiently by clustering feature points according to their temporal locations in the video is proposed. Moreover, shot representations are generated based on a variation of the spatial-temporal pyramid matching method using max-pooling and sparse coding of video features. The video can finally be presented by max-pooling shot representations again and be classified using a linear SVM. This framework is evaluated on the KTH and the UCF sports human action datasets and promising performances are obtained compared to state-of-the-art methods.

关键词： Feature extraction Vectors Encoding Computer vision conferences Detectors pattern recognition

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The combination of CSLBP and LBP feature for pedestrian detection

The combination of CSLBP and LBP feature for pedestrian dete...

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international conference on Computer Science and Network Technology (ICCSNT)

作者： Jingjing Li Yong Zhao Dongbing Quan Shenzhen Graduate School School of Electronic and Computer Engineering Peking University Shenzhen China

ISBN: (纸本)9781479905607

Local Binary pattern (LBP) feature has attracted increasing interest in pedestrian detection tasks, but it requires high dimensionality to gain promising performance. To address this problem, we make three main contributions. First, Center-Symmetric Local Binary patterns (CSLBP) feature is introduced to pedestrian detection. It's the first time to extract CSLBP operator in an approach similar to basic LBP operator. Second, we propose the operator combining CSLBP 1,8 pattern and uniform LBP 1,8 pattern, named combined-LBP descriptor for convenience. Third, the combined-LBP operator is applied to various color spaces. Experiments on INRIA pedestrian database show that combined-LBP operator based pedestrian detector achieve state of art performance with miss rate of 6.04% at FPPW=10 -4 in gray-scale image, and the proposed operator in oRGB color space obtain superior result with miss rate of 2.75% at FPPW=10 -4 .

关键词： Feature extraction Image color analysis Detectors Gray-scale pattern recognition Databases Histograms

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Efficient image appearance description using dense sampling based local binary patterns

Efficient image appearance description using dense sampling ...

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11th Asian conference on Computer Vision, ACCV 2012

作者： Ylioinas, Juha Hadid, Abdenour Guo, Yimo Pietikäinen, Matti Center for Machine Vision Research University of Oulu PO Box 4500 Oulu FI-90014 Finland

ISBN: (纸本)9783642374302

This work presents a novel image appearance description method based on the highly popular local binary pattern (LBP) texture features. The key idea consists of introducing a dense sampling encoding strategy for extracting more stable and discriminative texture patterns in local regions. Compared to the conventional "sparse" sampling scheme commonly used in basic LBP, our proposed dense sampling aims to generate, through a form of up-sampling, more neighboring pixels so that more stable LBP codes, carrying out richer information, are computed. This yields in significantly enhanced image description which is less prone to noise and to sparse and unstable histograms. Another interesting property of the dense sampling scheme is that it can be easily integrated with many existing LBP variants. Extensive experiments on three different classification problems namely face recognition, texture classification and age group estimation on various challenging benchmark databases clearly demonstrate the efficiency of the proposed scheme, showing very promising results compared not only to original LBP but also to state-of-the-art especially in the very demanding task of human age estimation. © 2013 Springer-Verlag.

关键词： Local binary pattern

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A Survey on Intelligent Information Processing System: A machine Ailment Diagnosing Based on KNN Similarity Degree

A Survey on Intelligent Information Processing System: A Mac...

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international conference on Computer Sciences and Applications (CSA)

作者： Xiping Wang Wenxue Tan School of Economics and Management Hunan University of Arts and Science Changde China Software Engineering Department NERCITA Beijing Academy of Agriculture and Forestry Sciences Beijing China

Intelligent Information Processing System has successful application in informationization of traditional industry. Exact addressing the stock case's ailment type and roots as quickly as possible has been the weight of developing information technology for veterinary. In order to assist human veterinarian expert diagnose animal ailment, this work proposes a machine diagnosing model based on KNN ailment-similarity-degree pattern recognition. The project crew devises 3 similarity distance measuring methods including Lee distance and Jaro distance, which are addressed to the uncertainty factor vector pattern and fuzzy membership pattern. In addition, the software architecture of the machine diagnosing model and diagnosing algorithm is constructed in detail. Field experimental statistics demonstrate that compared with the individual human veterinary expert, the proposed model achieve a preferable accuracy rate of diagnosis over 80%, and low a rate of misdiagnosis obviously, which is an alternate of existent ones with great potential.

关键词： Educational institutions pattern recognition Art Artificial intelligence Vectors Uncertainty Information processing

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A business protocol unit testing framework for Web service composition

A business protocol unit testing framework for Web service c...

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25th international conference on Advanced Information Systems Engineering, CAiSE 2013

作者： Yu, Jian Han, Jun Gunarso, Steven O. Versteeg, Steve Faculty of Information and Communication Technologies Swinburne University of Technology Melbourne VIC 3122 Australia CA Labs. 380 St. Kilda Rd Melbourne VIC 3004 Australia

ISBN: (纸本)9783642387081

Unit testing is a critical step in the development lifecycle of business processes for ensuring product reliability and dependability. Although plenty of unit testing approaches for WS-BPEL have been proposed, only a few of them designed and implemented a runnable unit testing framework, and none of them provides a technique to systematically specifying and testing the causal and temporal dependencies between the process-under-test and its partner services. In this paper, we propose a novel approach and framework for specifying and testing the inter-dependencies between the process-under-test and its partner services. The dependency constraints defined in the business protocol are declaratively specified using a pattern-based high-level language, and a FSA-based approach is proposed for detecting the violation of constraints. A testing framework that integrates with the Java Finite State machine framework has been implemented to support the specification of both dependency constraints and test cases, and the execution and result analysis of test cases. © 2013 Springer-Verlag.

关键词： High level languages

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An Interactive Rough Set Attribute Reduction Using Great Deluge Algorithm

An Interactive Rough Set Attribute Reduction Using Great Del...

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3rd international Visual Informatics conference (IVIC)

作者： Jaddi, Najmeh Sadat Abdullah, Salwani Univ Kebangsaan Malaysia Fac Informat Sci & Technol Data Min & Optimizat Res Grp DMO Ctr Artificial Intelligence Technol Bangi 43600 Selangor Malaysia

ISBN: (纸本)9783319029573;9783319029580

Dimensionality reduction from an information system is a problem of eliminating unimportant attributes from the original set of attributes while avoiding loss of information in data mining process. In this process, a subset of attributes that is highly correlated with decision attributes is selected. In this paper, performance of the great deluge algorithm for rough set attribute reduction is investigated by comparing the method with other available approaches in the literature in terms of cardinality of obtained reducts (subsets), time required to obtain reducts, number of calculating dependency degree functions, number of rules generated by reducts, and the accuracy of the classification. An interactive interface is initially developed that user can easily select the parameters for reduction. This user interface is developed toward visual data mining. The carried out model has been tested on the standard datasets available in the UCI machine learning repository. Experimental results show the effectiveness of the method especially with relation to the time and accuracy of the classification using generated rules. The method outperformed other approaches in M-of-N, Exactly, and LED datasets with achieving 100% accuracy.

关键词： interactive data mining great deluge algorithm rough set theory attribute reduction classification

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