Abstract:
We present a method for animating 3D models of animals from existing
live video sequences such as wild life documentaries. Videos are first
segmented into binary images on which Principal Component Analysis
(PCA) is applied. The time-varying coordinates of the images in the PCA
space are then used to generate 3D animation. This is done through
interpolation with Radial Basis Functions (RBF) of 3D pose examples
associated with a small set of key-images extracted from the video. In
addition to this processing pipeline, our main contributions are: an
automatic method for selecting the best set of key-images for which the
designer will need to provide 3D pose examples. This method saves user
time and effort since there is no more need for manual selection within
the video and then trials and errors in the choice of key-images and 3D
pose examples. As another contribution, we propose a simple algorithm
based on PCA images to resolve 3D pose prediction ambiguities. These
ambiguities are inherent to many animal gaits when only monocular view
is available.
The method is first evaluated on sequences of synthetic images of
animal gaits, for which full 3D data is available. We achieve a good
quality reconstruction of the input 3D motion from a single video
sequence of its 2D rendering. We then illustrate the method by
reconstructing animal gaits from live video of wild life documentaries.
Key words :
Animation from Motion/Video Data, Interpolation Keyframing, Intuitive
Interfaces for Animation.
Reference:
Favreau, L., Reveret, L., Depraz, C., Cani, MP., "
Animal Gaits From Video",
2004
ACM SIGGRAPH/Eurographics Symposium on Computer Animation,
Grenoble, France, August 2004. To appear.
Paper [PDF
6Mb]
Video [MPEG
29Mb]
