Temporally enhanced 3D capture of room-sized dynamic scenes with commodity depth cameras

Abstract

In this paper, we introduce a system to capture the enhanced 3D structure of a room-sized dynamic scene with commodity depth cameras such as Microsoft Kinects. It is challenging to capture the entire dynamic room. First, the raw data from depth cameras are noisy due to the conflicts of the room's large volume and cameras' limited optimal working distance. Second, the severe occlusions between objects lead to dramatic missing data in the captured 3D. Our system incorporates temporal information to achieve a noise-free and complete 3D capture of the entire room. More specifically, we pre-scan the static parts of the room offline, and track their movements online. For the dynamic objects, we perform non-rigid alignment between frames and accumulate data over time. Our system also supports the topology changes of the objects and their interactions. We demonstrate the success of our system with various situations.