Human Shape Estimation in a Multi-Camera Studio

This paper addresses the problem of estimating the shape of an actor in a multi-camera studio for arbitrarily positioned cameras and arbitrary human pose. We adopt a seamless articulated mesh model and introduce a novel shape matching technique to automatically transform the projected shape of the model to match multiple captured image silhouettes. Our approach treats the projected mesh as a deformable model and constrains the model to follow a smooth shape transformation to match each image silhouette. Multiple 2D transformations are integrated in 3D to update the shape of the model to match the actor. We assess the technique using virtual views generated for 3D scanned human data-sets and present preliminary results in a studio.