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170802 ||| eng |
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|a 9783319570211
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| 100 |
1 |
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|a Escalera, Sergio
|e [editor]
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| 245 |
0 |
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|a Gesture Recognition
|h Elektronische Ressource
|c edited by Sergio Escalera, Isabelle Guyon, Vassilis Athitsos
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2017, 2017
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| 300 |
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|a XII, 578 p. 214 illus., 170 illus. in color
|b online resource
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| 505 |
0 |
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|a Preface -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5
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| 653 |
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|a Computer Vision
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Automated Pattern Recognition
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| 653 |
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|a Computer vision
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| 653 |
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|a Pattern recognition systems
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| 700 |
1 |
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|a Guyon, Isabelle
|e [editor]
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| 700 |
1 |
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|a Athitsos, Vassilis
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a The Springer Series on Challenges in Machine Learning
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-57021-1
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-319-57021-1?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 006.3
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| 520 |
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|a 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
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