Human Body Posture Inference for Immersive Interaction
Abstract
We present an approach for inferring the body posture
from a 3D visual-hull representation. We present an appearance based,
view-independent, 3D shape description for classifying and
identifying human posture using a support vector machine. The
proposed global representation allows a robust description of shape
that accommodates for variation of the shape of the human body
across multiple people.
The proposed method does not require an
articulated body model fitted onto the reconstructed 3D geometry
of the human body: It complements the articulated body model
since we can define a mapping between the observed shape and the
learned descriptions for inferring the articulated body model. The
proposed method is illustrated on a set of body postures captured
by four cameras.