國立虎尾科技大學 |

Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications/ by Chiara Brombin, Luigi Salmaso, Lara Fontanella, Luigi Ippoliti, Caterina Fusilli.
作者:	Brombin, Chiara.
其他作者:	Salmaso, Luigi.
面頁冊數:	X, 115 p. 48 illus., 27 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Statistics . -
電子資源:	https://doi.org/10.1007/978-3-319-26311-3
ISBN:	9783319263113

Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
Brombin, Chiara.

Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications[electronic resource] /by Chiara Brombin, Luigi Salmaso, Lara Fontanella, Luigi Ippoliti, Caterina Fusilli. - 1st ed. 2016. - X, 115 p. 48 illus., 27 illus. in color.online resource. - SpringerBriefs in Statistics,2191-544X. - SpringerBriefs in Statistics,0.

Part I Offset Normal Distribution for Dynamic Shapes -- Basic Concepts and Definitions -- Shape Inference and the Offset-Normal Distribution -- Dynamic Shape Analysis Through the Offset-Normal Distribution -- Part II Combination-Based Permutation Tests for Shape Analysis -- Parametric and Non-Parametric Testing of Mean Shapes -- Applications of NPC Methodology -- Shape Inference and the Offset-Normal Distribution. .

This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain. The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out. Specifically, it works with the offset-normal shape distribution as a probability model for statistical inference on a sample of a temporal sequence of landmark configurations. This enables inference for Gaussian processes from configurations onto the shape space. The book is divided in two parts, with the first three chapters covering material on the offset-normal shape distribution, and the remaining chapters covering the theory of NonParametric Combination (NPC) tests. The chapters offer a collection of applications which are bound together by the theme of this book. They refer to the analysis of data from the FG-NET (Face and Gesture Recognition Research Network) database with facial expressions. For these data, it may be desirable to provide a description of the dynamics of the expressions, or testing whether there is a difference between the dynamics of two facial expressions or testing which of the landmarks are more informative in explaining the pattern of an expression. .

ISBN: 9783319263113

Standard No.: 10.1007/978-3-319-26311-3doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications
LDR:03477nam a22003975i 4500 001 972422
003 DE-He213
005 20200705033236.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319263113 $9 978-3-319-26311-3
024 7 $a 10.1007/978-3-319-26311-3 $2 doi
035 $a 978-3-319-26311-3
050 4 $a QA276-280
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
100 1 $a Brombin, Chiara. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1078644
245 1 0 $a Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications $h [electronic resource] / $c by Chiara Brombin, Luigi Salmaso, Lara Fontanella, Luigi Ippoliti, Caterina Fusilli.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a X, 115 p. 48 illus., 27 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Statistics, $x 2191-544X
505 0 $a Part I Offset Normal Distribution for Dynamic Shapes -- Basic Concepts and Definitions -- Shape Inference and the Offset-Normal Distribution -- Dynamic Shape Analysis Through the Offset-Normal Distribution -- Part II Combination-Based Permutation Tests for Shape Analysis -- Parametric and Non-Parametric Testing of Mean Shapes -- Applications of NPC Methodology -- Shape Inference and the Offset-Normal Distribution. .
520 $a This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain. The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out. Specifically, it works with the offset-normal shape distribution as a probability model for statistical inference on a sample of a temporal sequence of landmark configurations. This enables inference for Gaussian processes from configurations onto the shape space. The book is divided in two parts, with the first three chapters covering material on the offset-normal shape distribution, and the remaining chapters covering the theory of NonParametric Combination (NPC) tests. The chapters offer a collection of applications which are bound together by the theme of this book. They refer to the analysis of data from the FG-NET (Face and Gesture Recognition Research Network) database with facial expressions. For these data, it may be desirable to provide a description of the dynamics of the expressions, or testing whether there is a difference between the dynamics of two facial expressions or testing which of the landmarks are more informative in explaining the pattern of an expression. .
650 0 $a Statistics . $3 1253516
650 0 $a Mathematical statistics. $3 527941
650 0 $a Computer mathematics. $3 1199796
650 1 4 $a Statistical Theory and Methods. $3 671396
650 2 4 $a Probability and Statistics in Computer Science. $3 669886
650 2 4 $a Computational Mathematics and Numerical Analysis. $3 669338
700 1 $a Salmaso, Luigi. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1267566
700 1 $a Fontanella, Lara. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1267567
700 1 $a Ippoliti, Luigi. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1267568
700 1 $a Fusilli, Caterina. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1267569
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319263106
776 0 8 $i Printed edition: $z 9783319263120
830 0 $a SpringerBriefs in Statistics, $x 2191-544X ; $v 0 $3 1254767
856 4 0 $u https://doi.org/10.1007/978-3-319-26311-3
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)