Autocomplete Animated Sculpting

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DOI

Keyframe-based sculpting provides unprecedented freedom to author animated organic models, which can be difficult to create with other methods such as simulation, scripting, and rigging. However, sculpting animated objects can require significant artistic skill and manual labor, even more so than sculpting static 3D shapes or drawing 2D animations, which are already quite challenging. We present a keyframe-based animated sculpting system with the capability to autocomplete user editing under a simple and intuitive brushing interface. Similar to current desktop sculpting and VR brushing tools, users can brush surface details and volume structures. Meanwhile, our system analyzes their workflows and predicts what they might do in the future, both spatially and temporally. Users can accept or ignore these suggestions and thus maintain full control. We propose the first interactive suggestive keyframe sculpting system, specifically for spatio-temporal repetitive tasks, including low-level spatial details and high-level brushing structures across multiple frames. Our key ideas include a deformation-based optimization framework to analyze recorded workflows and synthesize predictions, and a semi-causal global similarity measurement to support flexible brushing stroke sequences and complex shape changes. Our system supports a variety of shape and motion styles, including those difficult to achieve via existing animation systems, such as topological changes that cannot be accomplished via simple rig-based deformations and stylized physically-implausible motions that cannot be simulated. We evaluate our system via a pilot user study that demonstrates the effectiveness of our system.