Performance Capture of High-Speed Motion Using Staggered Multi-View Recording

Abstract

We present a markerless performance capture system that can acquire the motion and the texture of human actors performing fast movements using only commodity hardware. To this end we introduce two novel concepts: First, a staggered surround multi-view recording setup that enables us to perform model-based motion capture on motion-blurred images, and second, a model-based deblurring algorithm which is able to handle disocclusion, self-occlusion and complex object motions. We show that the model-based approach is not only a powerful strategy for tracking but also for deblurring highly complex blur patterns.