Coverart for item
The Resource Gesture recognition, Sergio Escalera, Isabelle Guyon, Vassilis Athitsos, editors, (electronic resource)

Gesture recognition, Sergio Escalera, Isabelle Guyon, Vassilis Athitsos, editors, (electronic resource)

Label
Gesture recognition
Title
Gesture recognition
Statement of responsibility
Sergio Escalera, Isabelle Guyon, Vassilis Athitsos, editors
Contributor
Subject
Language
eng
Summary
This book presents a selection of chapters, written by leading international researchers, related to the automatic analysis of gestures from still images and multi-modal RGB-Depth image sequences. It offers a comprehensive review of vision-based approaches for supervised gesture recognition methods that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures
Member of
Dewey number
  • 006.4/2
  • 004
Index
no index present
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Escalera, Sergio
  • Guyon, Isabelle
  • Athitsos, Vassilis
Series statement
The Springer series on challenges in machine learning,
http://library.link/vocab/subjectName
  • Pattern recognition systems
  • Gesture
  • Machine learning
Label
Gesture recognition, Sergio Escalera, Isabelle Guyon, Vassilis Athitsos, editors, (electronic resource)
Instantiates
Publication
Contents
  • Foreword; Preface; Contents; 1 Challenges in Multi-modal Gesture Recognition; 1.1 Introduction; 1.2 Related Work in Gesture Recognition; 1.2.1 Taxonomy for Gesture Recognition; 1.2.2 Overview of Gesture Recognition Methods; 1.2.3 Sign Language Recognition; 1.2.4 Data Sets for Gesture and Action Recognition; 1.3 Gesture Recognition Challenges; 1.3.1 First ChaLearn Gesture Recognition Challenge (2011 -- 2012): One Shot Learning; 1.3.2 ChaLearn Multimodal Gesture Recognition Challenge 2013; 1.3.3 ChaLearn Multimodal Gesture Spotting Challenge 2014
  • 1.3.4 ChaLearn Action and Interaction Spotting Challenge 20141.3.5 ChaLearn Action and Interaction Spotting Challenge 2015; 1.3.6 Other International Competitions for Gesture and Action Recognition; 1.4 Summary of Special Topic Papers Not Related to the Challenges; 1.5 Summary of Special Topic Papers Related to 2011 -- 2012 Challenges; 1.6 Summary of Special Issue Papers Related to 2013 Challenge; 1.7 Discussion; References; 2 Human Gesture Recognition on Product Manifolds; 2.1 Introduction; 2.2 Related Work; 2.3 Mathematical Background ; 2.3.1 Tensor Representation; 2.3.2 Orthogonal Groups
  • 2.3.3 Stiefel Manifolds2.3.4 Grassmann Manifolds; 2.4 Elements of Product Manifolds ; 2.4.1 Product Manifolds; 2.4.2 Factorization in Product Spaces; 2.4.3 Geodesic Distance on Product Manifolds; 2.5 The Product Manifold Representation ; 2.6 Statistical Modeling; 2.6.1 Linear Least Squares Regression; 2.6.2 Least Squares Regression on Manifolds; 2.7 Experimental Results; 2.7.1 Cambridge Hand-Gesture Data Set; 2.7.2 UMD Keck Body-Gesture Data Set; 2.7.3 One-Shot-Learning Gesture Challenge; 2.8 Discussion; 2.9 Conclusions; References; 3 Sign Language Recognition Using Sub-units
  • 3.1 Introduction3.2 Background; 3.2.1 Linguistics; 3.3 Learning Appearance Based Sub-units; 3.3.1 Location Features; 3.3.2 Motion and Hand-Arrangement Moment Feature Vectors; 3.3.3 Motion Binary Patterns and Additive Classifiers; 3.4 2D Tracking Based Sub-units; 3.4.1 Motion Features; 3.4.2 Location Features; 3.4.3 HandShape Features; 3.4.4 HandShape Classifiers; 3.5 3D Tracking Based Sub-units; 3.5.1 Motion Features; 3.5.2 Location Features; 3.6 Sign Level Classification; 3.6.1 Markov Models; 3.6.2 SP Boosting; 3.7 Appearance Based Results; 3.8 2D Tracking Results; 3.9 3D Tracking Results
  • 3.9.1 Data Sets3.9.2 GSL Results; 3.9.3 DGS Results; 3.10 Discussion; 3.11 Conclusions; 3.12 Future Work; References; 4 MAGIC Summoning: Towards Automatic Suggesting and Testing of Gestures with Low Probability of False Positives During Use; 4.1 Introduction; 4.2 MAGIC Summoning Web-Based Toolkit; 4.2.1 Creating Gesture Classes and Testing for Confusion Between Classes; 4.2.2 Android Phone Accelerometer Everyday Gesture Library; 4.2.3 Testing for False Positives with the EGL; 4.3 False Positive Prediction; 4.3.1 Overview of EGL Search Method and Assumptions; 4.3.2 SAX Encoding
Control code
ocn994692397
Dimensions
unknown
Extent
1 online resource
Form of item
online
Isbn
9783319570211
Specific material designation
remote
System control number
(OCoLC)994692397
Label
Gesture recognition, Sergio Escalera, Isabelle Guyon, Vassilis Athitsos, editors, (electronic resource)
Publication
Contents
  • Foreword; Preface; Contents; 1 Challenges in Multi-modal Gesture Recognition; 1.1 Introduction; 1.2 Related Work in Gesture Recognition; 1.2.1 Taxonomy for Gesture Recognition; 1.2.2 Overview of Gesture Recognition Methods; 1.2.3 Sign Language Recognition; 1.2.4 Data Sets for Gesture and Action Recognition; 1.3 Gesture Recognition Challenges; 1.3.1 First ChaLearn Gesture Recognition Challenge (2011 -- 2012): One Shot Learning; 1.3.2 ChaLearn Multimodal Gesture Recognition Challenge 2013; 1.3.3 ChaLearn Multimodal Gesture Spotting Challenge 2014
  • 1.3.4 ChaLearn Action and Interaction Spotting Challenge 20141.3.5 ChaLearn Action and Interaction Spotting Challenge 2015; 1.3.6 Other International Competitions for Gesture and Action Recognition; 1.4 Summary of Special Topic Papers Not Related to the Challenges; 1.5 Summary of Special Topic Papers Related to 2011 -- 2012 Challenges; 1.6 Summary of Special Issue Papers Related to 2013 Challenge; 1.7 Discussion; References; 2 Human Gesture Recognition on Product Manifolds; 2.1 Introduction; 2.2 Related Work; 2.3 Mathematical Background ; 2.3.1 Tensor Representation; 2.3.2 Orthogonal Groups
  • 2.3.3 Stiefel Manifolds2.3.4 Grassmann Manifolds; 2.4 Elements of Product Manifolds ; 2.4.1 Product Manifolds; 2.4.2 Factorization in Product Spaces; 2.4.3 Geodesic Distance on Product Manifolds; 2.5 The Product Manifold Representation ; 2.6 Statistical Modeling; 2.6.1 Linear Least Squares Regression; 2.6.2 Least Squares Regression on Manifolds; 2.7 Experimental Results; 2.7.1 Cambridge Hand-Gesture Data Set; 2.7.2 UMD Keck Body-Gesture Data Set; 2.7.3 One-Shot-Learning Gesture Challenge; 2.8 Discussion; 2.9 Conclusions; References; 3 Sign Language Recognition Using Sub-units
  • 3.1 Introduction3.2 Background; 3.2.1 Linguistics; 3.3 Learning Appearance Based Sub-units; 3.3.1 Location Features; 3.3.2 Motion and Hand-Arrangement Moment Feature Vectors; 3.3.3 Motion Binary Patterns and Additive Classifiers; 3.4 2D Tracking Based Sub-units; 3.4.1 Motion Features; 3.4.2 Location Features; 3.4.3 HandShape Features; 3.4.4 HandShape Classifiers; 3.5 3D Tracking Based Sub-units; 3.5.1 Motion Features; 3.5.2 Location Features; 3.6 Sign Level Classification; 3.6.1 Markov Models; 3.6.2 SP Boosting; 3.7 Appearance Based Results; 3.8 2D Tracking Results; 3.9 3D Tracking Results
  • 3.9.1 Data Sets3.9.2 GSL Results; 3.9.3 DGS Results; 3.10 Discussion; 3.11 Conclusions; 3.12 Future Work; References; 4 MAGIC Summoning: Towards Automatic Suggesting and Testing of Gestures with Low Probability of False Positives During Use; 4.1 Introduction; 4.2 MAGIC Summoning Web-Based Toolkit; 4.2.1 Creating Gesture Classes and Testing for Confusion Between Classes; 4.2.2 Android Phone Accelerometer Everyday Gesture Library; 4.2.3 Testing for False Positives with the EGL; 4.3 False Positive Prediction; 4.3.1 Overview of EGL Search Method and Assumptions; 4.3.2 SAX Encoding
Control code
ocn994692397
Dimensions
unknown
Extent
1 online resource
Form of item
online
Isbn
9783319570211
Specific material designation
remote
System control number
(OCoLC)994692397

Library Locations

    • InternetBorrow it
      Albany, Auckland, 0632, NZ
Processing Feedback ...