Virtual view synthesis of people from multiple view video sequences

This paper addresses the synthesis of novel views of people from multiple view video. We consider the target area of the multiple camera 3D Virtual Studio for broadcast production with the requirement for free-viewpoint video synthesis for a virtual camera with the same quality as captured video. A framework is introduced for view-dependent optimisation of reconstructed surface shape to align multiple captured images with sub-pixel accuracy for rendering novel views. View-dependent shape optimisation combines multiple view stereo and silhouette constraints to robustly estimate correspondence between images in the presence of visual ambiguities such as uniform surface regions, self-occlusion, and camera calibration error. Free-viewpoint rendering of video sequences of people achieves a visual quality comparable to the captured video images. Experimental evaluation demonstrates that this approach overcomes limitations of previous stereo- and silhouette-based approaches to rendering novel views of moving people.