Lions and Tigers and Bears:
Capturing Non-Rigid, 3D, Articulated Shape from Images
Abstract
Animals are widespread in nature and the analysis of
their shape and motion is important in many fields and industries. Modeling 3D animal shape, however, is difficult
because the 3D scanning methods used to capture human
shape are not applicable to wild animals or natural settings.
Consequently, we propose a method to capture the detailed
3D shape of animals from images alone. The articulated
and deformable nature of animals makes this problem extremely challenging, particularly in unconstrained environments with moving and uncalibrated cameras. To make this
possible, we use a strong prior model of articulated animal
shape that we fit to the image data. We then deform the animal shape in a canonical reference pose such that it matches
image evidence when articulated and projected into multiple images. Our method extracts significantly more 3D
shape detail than previous methods and is able to model
new species, including the shape of an extinct animal, using only a few video frames. Additionally, the projected 3D
shapes are accurate enough to facilitate the extraction of a
realistic texture map from multiple frames