Sketch2Pose: estimating a 3D character pose from a bitmap sketch
Kirill Brodt, Mikhail Bessmeltsev
View presentation:2022-10-19T16:33:00ZGMT-0600Change your timezone on the schedule page
2022-10-19T16:33:00Z
Prerecorded Talk
The live footage of the talk, including the Q&A, can be viewed on the session page, SIGGRAPH Invited Talks.
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Keywords
Character posing, rigged and skinned characters, sketch-based posing, character sketches
Abstract
Artists frequently capture character poses via raster sketches, then use these drawings as a reference while posing a 3D character in a specialized 3D software --- a time-consuming process, requiring specialized 3D training and mental effort. We tackle this challenge by proposing the first system for automatically inferring a 3D character pose from a single bitmap sketch, producing poses consistent with viewer expectations. Algorithmically interpreting bitmap sketches is challenging, as they contain significantly distorted proportions and foreshortening. We address this by predicting three key elements of a drawing, necessary to disambiguate the drawn poses: 2D bone tangents, self-contacts, and bone foreshortening. These elements are then leveraged in an optimization inferring the 3D character pose consistent with the artist's intent. Our optimization balances cues derived from artistic literature and perception research to compensate for distorted character proportions. We demonstrate a gallery of results on sketches of numerous styles. We validate our method via numerical evaluations, user studies, and comparisons to manually posed characters and previous work. Code and data for our paper are available at http://www-labs.iro.umontreal.ca/bmpix/sketch2pose/.