Motion Matching for Character Animation and Virtual Reality Avatars in Unity

Real-time animation of virtual characters has traditionally been accomplished by playing short sequences of animations structured in the form of a graph. These methods are time-consuming to set up and scale poorly with the number of motions required in modern virtual environments. The ever-increasin...

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Detalles Bibliográficos
Autor: Pontón Martínez, José Luis|||0000-0001-6576-4528
Tipo de recurso: tesis de maestría
Fecha de publicación:2022
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/372815
Acceso en línea:https://hdl.handle.net/2117/372815
Access Level:acceso abierto
Palabra clave:Virtual reality
Computer animation
Machine learning
Animació per Computador
Realitat Virtual
Avatars
Aprenentatge Automàtic
Captura de Moviments
Computer Animation
Virtual Reality
Machine Learning
Motion Capture
Realitat virtual
Animació per ordinador
Aprenentatge automàtic
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
Descripción
Sumario:Real-time animation of virtual characters has traditionally been accomplished by playing short sequences of animations structured in the form of a graph. These methods are time-consuming to set up and scale poorly with the number of motions required in modern virtual environments. The ever-increasing need for highly-realistic virtual characters in fields such as entertainment, virtual reality, or the metaverse has led to significant advances in the field of data-driven character animation. Techniques like Motion Matching have provided enough versatility to conveniently animate virtual characters using a selection of features from an animation database. Data-driven methods retain the quality of the captured animations, thus delivering smoother and more natural-looking animations. In this work, we researched and developed a Motion Matching technique for the Unity game engine. In this thesis, we present our findings on how to implement an animation system based on Motion Matching. We also introduce a novel method combining body orientation prediction with Motion Matching to animate avatars for consumer-grade virtual reality systems.