Cage-based Performance Capture:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
2014
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| Schriftenreihe: | Studies in Computational Intelligence
509 |
| Schlagworte: | |
| Online-Zugang: | BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 UBY01 Volltext Inhaltsverzeichnis Abstract |
| Beschreibung: | 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 |
| Beschreibung: | 1 Online-Ressource (X, 141 p.) 86 illus., 85 illus. in color |
| ISBN: | 9783319015385 |
| DOI: | 10.1007/978-3-319-01538-5 |
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| 500 | |a 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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| adam_text | CAGE-BASED PERFORMANCE CAPTURE
/ SAVOYE, YANN
: 2014
TABLE OF CONTENTS / INHALTSVERZEICHNIS
GENERAL INTRODUCTION
SPARSE CONSTRAINTS OVER ANIMATABLE SUBSPACES
REUSING PERFORMANCE CAPTURE DATA
TOWARD NON-RIGID DYNAMIC CAGE CAPTURE
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
CAGE-BASED PERFORMANCE CAPTURE
/ SAVOYE, YANN
: 2014
ABSTRACT / INHALTSTEXT
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
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
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| indexdate | 2024-08-01T10:55:28Z |
| institution | BVB |
| isbn | 9783319015385 |
| language | English |
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| series | Studies in Computational Intelligence |
| series2 | Studies in Computational Intelligence |
| spellingShingle | Savoye, Yann Cage-based Performance Capture Studies in Computational Intelligence General Introduction -- Sparse Constraints Over Animatable Subspaces -- Reusing Performance Capture Data -- Toward Non-Rigid Dynamic Cage Capture Engineering Artificial intelligence Computer vision Computational Intelligence Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision Ingenieurwissenschaften Künstliche Intelligenz |
| title | Cage-based Performance Capture |
| title_auth | Cage-based Performance Capture |
| title_exact_search | Cage-based Performance Capture |
| title_full | Cage-based Performance Capture by Yann Savoye |
| title_fullStr | Cage-based Performance Capture by Yann Savoye |
| title_full_unstemmed | Cage-based Performance Capture by Yann Savoye |
| title_short | Cage-based Performance Capture |
| title_sort | cage based performance capture |
| topic | Engineering Artificial intelligence Computer vision Computational Intelligence Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision Ingenieurwissenschaften Künstliche Intelligenz |
| topic_facet | Engineering Artificial intelligence Computer vision Computational Intelligence Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision Ingenieurwissenschaften Künstliche Intelligenz |
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