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Computational Intelligence for Multimedia Understanding

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Cover of 'Computational Intelligence for Multimedia Understanding'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Learning an Ontology for Visual Tasks
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    Chapter 2 Ontology and Algorithms Integration for Image Analysis
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    Chapter 3 EmotiWord: Affective Lexicon Creation with Application to Interaction and Multimedia Data
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    Chapter 4 A Bayesian Active Learning Framework for a Two-Class Classification Problem
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    Chapter 5 Unsupervised Classification of SAR Images Using Hierarchical Agglomeration and EM
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    Chapter 6 Geometrical and Textural Component Separation with Adaptive Scale Selection
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    Chapter 7 Bayesian Shape from Silhouettes
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    Chapter 8 Shape Retrieval and Recognition on Mobile Devices
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    Chapter 9 Directionally Selective Fractional Wavelet Transform Using a 2-D Non-separable Unbalanced Lifting Structure
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    Chapter 10 Visible and Infrared Image Registration Employing Line-Based Geometric Analysis
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    Chapter 11 Texture Recognition Using Robust Markovian Features
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    Chapter 12 A Plausible Texture Enlargement and Editing Compound Markovian Model
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    Chapter 13 Bidirectional Texture Function Simultaneous Autoregressive Model
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    Chapter 14 Analysis of Human Gaze Interactions with Texture and Shape
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    Chapter 15 Rich Internet Application for Semi-automatic Annotation of Semantic Shots on Keyframes
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    Chapter 16 Labeling TV Stream Segments with Conditional Random Fields
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    Chapter 17 Foreground Objects Segmentation for Moving Camera Scenarios Based on SCGMM
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    Chapter 18 Real Time Image Analysis for Infomobility
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    Chapter 19 Tracking the Saliency Features in Images Based on Human Observation Statistics
Attention for Chapter 19: Tracking the Saliency Features in Images Based on Human Observation Statistics
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Chapter title
Tracking the Saliency Features in Images Based on Human Observation Statistics
Chapter number 19
Book title
Computational Intelligence for Multimedia Understanding
Published by
Springer, Berlin, Heidelberg, December 2011
DOI 10.1007/978-3-642-32436-9_19
Book ISBNs
978-3-64-232435-2, 978-3-64-232436-9
Authors

Szilard Szalai, Tamás Szirányi, Zoltan Vidnyanszky

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 50%
Student > Ph. D. Student 1 50%
Readers by discipline Count As %
Engineering 1 50%
Unknown 1 50%