1001 acquisition viewpoints: efficient and versatile view-dependent modeling of real-world scenes

Constructing high-fidelity 3D models of real-world scenes is an important bottleneck for many computer graphics applications. Manual modeling using CAD or animation software requires artistic talent and a huge time investment. Automated modeling based on acquiring color and depth data is a promising alternative. The typical automated modeling approach densely samples the color and geometry of the scene from several acquisition viewpoints, and then merges the datasets to obtain the scene model. However, dense depth sampling of complex scenes remains a challenging process that can take tens of minutes per acquisition viewpoint (e.g. sequential scanning in laser range finding, robust off-line correspondence computation in depth from stereo, or sequential light pattern projection in depth from structured light). This limits acquisition to a sparse set of viewpoints, and, even with careful view planning, complex scenes remain inadequately sampled.