“Cage-based Performance Capture” by Savoye

  • ©Yann Savoye

Conference:


Entry Number: 18

Title:

    Cage-based Performance Capture

Course Organizer(s):



Presenter(s):



Abstract:


    Nowadays, highly-detailed animations of live-actor performances are increasingly easier to acquire, and 3D Video has reached considerable attention in visual media productions. This lecture will address new paradigm to achieve performance capture using cage-based shapes in motion. We define cage-based performance capture as the non-invasive process of capturing non-rigid surface of actors from multi-view in the form of sparse control deformation handles trajectories and a laser-scanned static template shape.

    In this course, we address the hard problem of extracting or acquiring and then reusing non-rigid parametrization for video-based animations in four steps: (1) cage-based inverse kinematics, (2) conversion of surface performance capture into cage-based deformation, (3) cage-based cartoon surface exaggeration, and (4) cage-based registration of time-varying reconstructed point clouds. The key objective is to attract the interest of game programmers, digital artists and filmmakers in employing purely geometric and animator-friendly tools to capture and reuse surfaces in motion. Finally, a variety of advanced animation techniques and vision-based graphics applications could benefit from animatable coordinates-based sub-spaces as presented in this course.

    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. While abandoning the classical articulated skeleton as the underlying structure, we show that cage-based deformers offer a flexible design space abstraction to dynamically non-rigid surface motion through learning space-time shape variability. Registered cage-handles trajectories allow the reconstruction of complex mesh sequences by deforming an enclosed fine-detail mesh. Finally, cage-based performance capture techniques offer suitable and reusable outputs for animation transfer by decoupling the motion from the geometry.

    Prerequisites
    The only prerequisites are a basic knowledge in computer graphics, computer vision, and animation.

    Level
    Intermediate

    Intended Audience
    This is designed for an intermediate audience.

    Description
    This course addresses techniques to achieve performance capture using cage-based shapes in motion. We define cage-based performance capture as the non-invasive process of capturing non-rigid surface of actors from multi-view in the form of sparse control deformation handles trajectories and a laser-scanned template shape.


ACM Digital Library Publication:


Overview Page:



Type: