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Image Processing Theory Tools and Applications (IPTA), 2010 2nd International Conference on

Date 7-10 July 2010

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Displaying Results 1 - 25 of 123
  • [Title page]

    Publication Year: 2010 , Page(s): 1
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  • Foreword

    Publication Year: 2010 , Page(s): 1
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  • Sponsors and supports

    Publication Year: 2010 , Page(s): 1
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  • Organizing and scientific Program Committees

    Publication Year: 2010 , Page(s): 1 - 2
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  • Table of contents

    Publication Year: 2010 , Page(s): 1 - 7
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  • Invited speakers

    Publication Year: 2010 , Page(s): 1
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (14 KB)  

    Provides an abstract for each of the invited presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • Indexing of compressed video: Methods, challenges, applications

    Publication Year: 2010 , Page(s): 3 - 4
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  • Multidimensional particle swarm optimization and applications in data clustering and image retrieval

    Publication Year: 2010 , Page(s): 5
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  • Distributed Video Coding: Status, challenges and outlook

    Publication Year: 2010 , Page(s): 6 - 7
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  • Augmented Reality: Issues, trends and challenges

    Publication Year: 2010 , Page(s): 8
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  • Tutorials

    Publication Year: 2010 , Page(s): 9
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  • Image and video descriptors

    Publication Year: 2010 , Page(s): 11 - 12
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  • H.264 video watermarking: Applications, principles, deadlocks and future

    Publication Year: 2010 , Page(s): 13
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  • Medical image analysis using high-dimensional information-theoretic criteria

    Publication Year: 2010 , Page(s): 14
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  • GDR-ISIS special session on feature selection and kernel methods for image classification, image segmentation and pattern recognition

    Publication Year: 2010 , Page(s): 15
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  • Fusion and classification of multi-source images by SVM with selected features in a kernel space

    Publication Year: 2010 , Page(s): 17 - 20
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (711 KB) |  | HTML iconHTML  

    The objective of this study concerns the classification of a scene observed by different types of images, which generates large amounts of data to be processed. We have therefore chosen to use the classification SVM (Support Vector Machines) who is known for treating high-dimensional data. Although different sources of information can provide additional information to address the ambiguities, they... View full abstract»

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  • Feature subspaces selection via one-class SVM: Application to textured image segmentation

    Publication Year: 2010 , Page(s): 21 - 25
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1036 KB) |  | HTML iconHTML  

    This paper presents a feature subspaces selection method which uses an ensemble of one-class SVMs. The objective is to improve or preserve the performance of a decision system in the presence of noise, loss of information or feature non-stationarity. The proposed method consists in first generating an ensemble of feature subspaces from the initial full-dimensional space, and then making the decisi... View full abstract»

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  • Adaptive feature selection for heterogeneous image databases

    Publication Year: 2010 , Page(s): 26 - 31
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (606 KB) |  | HTML iconHTML  

    Various visual characteristics based discriminative classification has become a standard technique for image recognition tasks in heterogeneous databases. Nevertheless, the encountered problem is the choice of the most relevant features depending on the considered image database content. In this aim, feature selection methods are used to remove the effect of the outlier features. Therefore, they a... View full abstract»

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  • Comparison of feature selection schemes for color texture classification

    Publication Year: 2010 , Page(s): 32 - 37
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (899 KB) |  | HTML iconHTML  

    In this paper, we propose to compare the performances of two sequential feature selection schemes used for supervised color texture classification. We focus this study on the sequential forward selection (SFS) scheme and the more complex sequential forward floating selection (SFFS) scheme which avoids the “nesting effect”. These schemes retain Haralick features extracted from chromat... View full abstract»

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  • Connectivity feature extraction for spatio-functional clustering of fMRI data

    Publication Year: 2010 , Page(s): 38 - 43
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1406 KB) |  | HTML iconHTML  

    As fMRI data is high dimensional, applications like connectivity studies, normalization or multivariate analyses, need to reduce data dimension while minimizing the loss of functional information. In our study we use connectivity profiles as a new functional feature to aggregate voxels into clusters. This offers two major advantages in comparison with the current clustering methods. It allows the ... View full abstract»

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  • Special session on video surveillance: Tools and applications

    Publication Year: 2010 , Page(s): 44
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  • Audio-video surveillance system for public transportation

    Publication Year: 2010 , Page(s): 47 - 53
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1148 KB) |  | HTML iconHTML  

    Focusing on improving security in public transports (here: trains), this paper presents a research project implementing an audio-video surveillance system. Combining audio analysis, video tracking and dedicated integration of audio-video acquisition and storage equipments, the proposed system addresses the task of providing an operator with a partially-supervised tool for tracking suspected person... View full abstract»

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  • Pedestrian detection based on adaboost algorithm with a pseudo-calibrated camera

    Publication Year: 2010 , Page(s): 54 - 59
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2128 KB) |  | HTML iconHTML  

    This paper presents a new algorithm for pedestrian detection for a fixed camera using the cluster boosted tree (CBT) structure of Wu and Nevatia for building a multi-view tree classifier based on edgelet features. The main advantage of this structure is that it is less sensitive to camera view changes compared to the cascade structure of Viola and Jones. The approach presented in this paper uses g... View full abstract»

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  • People re-identification by classification of silhouettes based on sparse representation

    Publication Year: 2010 , Page(s): 60 - 65
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (976 KB) |  | HTML iconHTML  

    The research presented in this paper consists in developing an automatic system for people re-identification across multiple cameras with non-overlapping fields of view. We first propose a robust algorithm for silhouette extraction which is based on an adaptive spatio-colorimetric background and foreground model coupled with a dynamic decision framework. Such a method is able to deal with the diff... View full abstract»

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  • A benchmark for Background Subtraction Algorithms in monocular vision: A comparative study

    Publication Year: 2010 , Page(s): 66 - 71
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1793 KB) |  | HTML iconHTML  

    Background subtraction of video sequences is mainly regarded as a solved problem. However, no complete benchmark about Background Subtraction Algorithms (BSA) has been established, with ground truth and associated quality measures. One of the reasons is that such comparative study needs annotated datasets. In this article, we propose a BSA evaluation dataset built from realistic synthetic image an... View full abstract»

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