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Kategorie szczegółowe BISAC

Cage-Based Performance Capture

ISBN-13: 9783319015378 / Angielski / Twarda / 2013 / 141 str.

Yann Savoye
Cage-Based Performance Capture Savoye, Yann 9783319015378 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Cage-Based Performance Capture

ISBN-13: 9783319015378 / Angielski / Twarda / 2013 / 141 str.

Yann Savoye
cena 401,58
(netto: 382,46 VAT:  5%)

Najniższa cena z 30 dni: 385,52
Termin realizacji zamówienia:
ok. 16-18 dni roboczych.

Darmowa dostawa!

Nowadays, highly-detailed animations of live-actor performances are increasingly easier to acquire and 3D Video has reached considerable attentions in visual media production. In this book, we address the problem of extracting or acquiring and then reusing non-rigid parametrization for video-based animations. At first sight, a crucial challenge is to reproduce plausible boneless deformations while preserving global and local captured properties of dynamic surfaces with a limited number of controllable, flexible and reusable parameters. To solve this challenge, we directly rely on a skin-detached dimension reduction thanks to the well-known cage-based paradigm. First, we achieve Scalable Inverse Cage-based Modeling by transposing the inverse kinematics paradigm on surfaces. Thus, we introduce a cage inversion process with user-specified screen-space constraints. Secondly, we convert non-rigid animated surfaces into a sequence of optimal cage parameters via Cage-based Animation Conversion. Building upon this reskinning procedure, we also develop a well-formed Animation Cartoonization algorithm for multi-view data in term of cage-based surface exaggeration and video-based appearance stylization. Thirdly, motivated by the relaxation of prior knowledge on the data, we propose a promising unsupervised approach to perform Iterative Cage-based Geometric Registration. This novel registration scheme deals with reconstructed target point clouds obtained from multi-view video recording, in conjunction with a static and wrinkled template mesh. Above all, we demonstrate the strength of cage-based subspaces in order to reparametrize highly non-rigid dynamic surfaces, without the need of secondary deformations. To the best of our knowledge this book opens the field of Cage-based Performance Capture.

Kategorie:
Informatyka
Kategorie BISAC:
Computers > Software Development & Engineering - Computer Graphics
Technology & Engineering > Engineering (General)
Computers > Artificial Intelligence - General
Wydawca:
Springer
Seria wydawnicza:
Studies in Computational Intelligence
Język:
Angielski
ISBN-13:
9783319015378
Rok wydania:
2013
Wydanie:
2014
Numer serii:
000318395
Ilość stron:
141
Waga:
3.55 kg
Wymiary:
23.5 x 15.5
Oprawa:
Twarda
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

General Introduction.- Sparse Constraints Over Animatable Subspaces.- Reusing Performance Capture Data.- Toward Non-Rigid Dynamic Cage Capture.

Nowadays, highly-detailed animations of live-actor performances are increasingly easier to acquire and 3D Video has reached considerable attentions in visual media production. In this book, we address the problem of extracting or acquiring and then reusing non-rigid parametrization for video-based animations. At first sight, a crucial challenge is to reproduce plausible boneless deformations while preserving global and local captured properties of dynamic surfaces with a limited number of controllable, flexible and reusable parameters. To solve this challenge, we directly rely on a skin-detached dimension reduction thanks to the well-known cage-based paradigm. First, we achieve Scalable Inverse Cage-based Modeling by transposing the inverse kinematics paradigm on surfaces. Thus, we introduce a cage inversion process with user-specified screen-space constraints. Secondly, we convert non-rigid animated surfaces into a sequence of optimal cage parameters via Cage-based Animation Conversion. Building upon this reskinning procedure, we also develop a well-formed Animation Cartoonization algorithm for multi-view data in term of cage-based surface exaggeration and video-based appearance stylization. Thirdly, motivated by the relaxation of prior knowledge on the data, we propose a promising unsupervised approach to perform Iterative Cage-based Geometric Registration. This novel registration scheme deals with reconstructed target point clouds obtained from multi-view video recording, in conjunction with a static and wrinkled template mesh. Above all, we demonstrate the strength of cage-based subspaces in order to reparametrize highly non-rigid dynamic surfaces, without the need of secondary deformations. To the best of our knowledge this book opens the field of Cage-based Performance Capture.



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