Lions and tigers and bears: Capturing non-rigid, 3D, articulated shape from images
Contributo in Atti di convegno
Data di Pubblicazione:
2018
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.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
3D shape model; 3D animal models
Elenco autori:
Zuffi, Silvia
Link alla scheda completa:
Titolo del libro:
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition CVPR 2018