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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction : Third IAPR TC3 Workshop, MPRSS 2014, Stockholm, Sweden, August 24, 2014, Revised Selected Papers

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Cover of 'Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction : Third IAPR TC3 Workshop, MPRSS 2014, Stockholm, Sweden, August 24, 2014, Revised Selected Papers'

Table of Contents

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    Book Overview
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    Chapter 1 Automatic Image Collection of Objects with Similar Function by Learning Human Grasping Forms
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    Chapter 2 Client Specific Image Gradient Orientation for Unimodal and Multimodal Face Representation
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    Chapter 3 Multiple-manifolds Discriminant Analysis for Facial Expression Recognition from Local Patches Set
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    Chapter 4 Monte Carlo Based Importance Estimation of Localized Feature Descriptors for the Recognition of Facial Expressions
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    Chapter 5 Noisy Speech Recognition Based on Combined Audio-Visual Classifiers
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    Chapter 6 Complementary Gaussian Mixture Models for Multimodal Speech Recognition
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    Chapter 7 Fusion of Text and Audio Semantic Representations Through CCA
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    Chapter 8 uulmMAD – A Human Action Recognition Dataset for Ground-Truth Evaluation and Investigation of View Invariances
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    Chapter 9 A Real Time Gesture Recognition System for Human Computer Interaction
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    Chapter 10 A SIFT-Based Feature Level Fusion of Iris and Ear Biometrics
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    Chapter 11 Audio-Visual User Identification in HCI Scenarios
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    Chapter 12 Towards an Adaptive Brain-Computer Interface – An Error Potential Approach
  14. Altmetric Badge
    Chapter 13 Online Smart Face Morphing Engine with Prior Constraints and Local Geometry Preservation
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    Chapter 14 Exploring Alternate Modalities for Tag Recommendation
Attention for Chapter 11: Audio-Visual User Identification in HCI Scenarios
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Chapter title
Audio-Visual User Identification in HCI Scenarios
Chapter number 11
Book title
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction
Published in
Lecture notes in computer science, August 2014
DOI 10.1007/978-3-319-14899-1_11
Book ISBNs
978-3-31-914898-4, 978-3-31-914899-1
Authors

Markus Kächele, Sascha Meudt, Andrej Schwarz, Friedhelm Schwenker

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Researcher 1 33%
Student > Postgraduate 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Psychology 1 33%
Engineering 1 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 January 2015.
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#18,388,295
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Outputs from Lecture notes in computer science
#6,005
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#168,282
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Outputs of similar age from Lecture notes in computer science
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