KinectFusion is a well-known 3D scanner powered by Microsoft’s Kinect camera. It has recently found its way into the official Kinect for Windows SDK. While KinectFusion produces very high-quality scans in real-time, it is limited to reconstructing small spaces (at most 4 x 4 x 4 meters).
In this paper Jiawen Chen, Shahram Izadi and I extended KinectFusion with a hierarchical data structure and streaming. This allows us to scan areas of virtually infinite size while maintaining the quality and performance of the original algorithm.
(Imrod walk cycle: 3M voxels, 36fps, GeForce GTX 460, 800×550 pixels, phong shading, normal mapping, shadow mapping, hardware skinning. Original model by Dmitry Parkin)
Sparse Voxel Octree (SVO) is one among many representations for 3D objects – Triangle Mesh being the most famous one due to its widespread use in the Real-time domain. SVOs have many advantages over triangle meshes, like implicit level of detail, dense representation, simpler intersection tests, simpler uv mapping.
Their biggest disadvantage (apart form the lack of a hardware-accelerated rendering pipeline) was the infeasibility of animating them. I tackled this problem in my bachelor thesis. The animation technique I developed makes