We present a novel hybrid representation for character animation from 4D Performance Capture (4DPC) data which combines skeletal control with surface motion graphs. 4DPC data are temporally aligned 3D mesh sequence reconstructions of the dynamic surface shape and associated appearance from multiple-view video. The hybrid representation supports the production of novel surface sequences which satisfy constraints from user-specified key-frames or a target skeletal motion. Motion graph path optimisation concatenates fragments of 4DPC data to satisfy the constraints while maintaining plausible surface motion at transitions between sequences. Space-time editing of the mesh sequence using a learned part-based Laplacian surface deformation model is performed to match the target skeletal motion and transition between sequences. The approach is quantitatively evaluated for three 4DPC datasets with a variety of clothing styles. Results for key-frame animation demonstrate production of novel sequences that satisfy constraints on timing and position of less than 1% of the sequence duration and path length. Evaluation of motion-capture-driven animation over a corpus of 130 sequences shows that the synthesised motion accurately matches the target skeletal motion. The combination of skeletal control with the surface motion graph extends the range and style of motion which can be produced while maintaining the natural dynamics of shape and appearance from the captured performance.

Surface motion capture (Surf Cap) enables 3D reconstruction of human performance with detailed cloth and hair deformation. However, there is a lack of tools that allow flexible editing of Surf Cap sequences. In this paper, we present a Laplacian editing technique that constrains the mesh deformation to plausible surface shapes learnt from a set of examples. A part-Based representation of the mesh enables learning of surface deformation locally in the space of Laplacian coordinates, avoiding correlations between body parts while preserving surface details. This extends the range of animation with natural surface deformation beyond the whole-body poses present in the Surf Cap data. We illustrate successful use of our tool on three different characters.

Surface motion capture (SurfCap) of actor performance from multiple view video provides reconstruction of the natural nonrigid deformation of skin and clothing. This paper introduces techniques for interactive animation control of SurfCap sequences which allow the flexibility in editing and interactive manipulation associated with existing tools for animation from skeletal motion capture (MoCap). Laplacian mesh editing is extended using a basis model learned from SurfCap sequences to constrain the surface shape to reproduce natural deformation. Three novel approaches for animation control of SurfCap sequences, which exploit the constrained Laplacian mesh editing, are introduced: 1) space–time editing for interactive sequence manipulation; 2) skeleton-driven animation to achieve natural nonrigid surface deformation; and 3) hybrid combination of skeletal MoCap driven and SurfCap sequence to extend the range of movement. These approaches are combined with high-level parametric control of SurfCap sequences in a hybrid surface and skeleton-driven animation control framework to achieve natural surface deformation with an extended range of movement by exploiting existing MoCap archives. Evaluation of each approach and the integrated animation framework are presented on real SurfCap sequences for actors performing multiple motions with a variety of clothing styles. Results demonstrate that these techniques enable flexible control for interactive animation with the natural nonrigid surface dynamics of the captured performance and provide a powerful tool to extend current SurfCap databases by incorporating new motions from MoCap sequences.

A 4D parametric motion graph representation is presented for interactive animation from actor performance capture in a multiple camera studio. The representation is based on a 4D model database of temporally aligned mesh sequence reconstructions for multiple motions. High-level movement controls such as speed and direction are achieved by blending multiple mesh sequences of related motions. A real-time mesh sequence blending approach is introduced, which combines the realistic deformation of previous nonlinear solutions with efficient online computation. Transitions between different parametric motion spaces are evaluated in real time based on surface shape and motion similarity. Four-dimensional parametric motion graphs allow real-time interactive character animation while preserving the natural dynamics of the captured performance.

A 4D parametric motion graph representation is presented for interactive animation from actor performance capture in a multiple camera studio. The representation is based on a 4D model database of temporally aligned mesh sequence reconstructions for multiple motions. High-level movement controls such as speed and direction are achieved by blending multiple mesh sequences of related motions. A real-time mesh sequence blending approach is introduced which combines the realistic deformation of previous non-linear solutions with efficient online computation. Transitions between different parametric motion spaces are evaluated in real-time based on surface shape and motion similarity. 4D parametric motion graphs allow real-time interactive character animation while preserving the natural dynamics of the captured performance.

ABSTRACT In this paper, we introduce an approach to high‐level parameterisation of captured mesh sequences of actor performance for real‐time interactive animation control. High‐level parametric control is achieved by non‐linear blending between multiple mesh sequences exhibiting variation in a particular movement. For example, walking speed is parameterised by blending fast and slow walk sequences. A hybrid non‐linear mesh sequence blending approach is introduced to approximate the natural deformation of non‐linear interpolation techniques whilst maintaining the real‐time performance of linear mesh blending. Quantitative results show that the hybrid approach gives an accurate real‐time approximation of offline non‐linear deformation. An evaluation of the approach shows good performance not only for entire meshes but also with specific mesh areas. Results are presented for single and multi‐dimensional parametric control of walking (speed/direction), jumping (height/distance) and reaching (height) from captured mesh sequences. This approach allows continuous real‐time control of high‐level parameters such as speed and direction whilst maintaining the natural surface dynamics of captured movement. Copyright © 2012 John Wiley & Sons, Ltd.