DTAM: Dense Tracking and Mapping in Real-Time

DTAM is a system for real-time camera tracking and reconstruction which relies not on feature extraction but dense, every pixel methods. As a single hand-held RGB camera flies over a static scene, we estimate detailed textured depth maps at selected keyframes to produce a surface patchwork with millions of vertices. We use the hundreds of images available in a video stream to improve the quality of a simple photometric data term, and minimise a global spatially regularised energy functional in a novel non-convex optimisation framework. Interleaved, we track the camera’s 6DOF motion precisely by frame-rate whole image alignment against the entire dense model. Our algorithms are highly parallelisable throughout and DTAM achieves realtime performance using current commodity GPU hardware. We demonstrate that a dense model permits superior tracking performance under rapid motion compared to a state of the art method using features; and also show the additional usefulness of the dense mo...

• Type: Journal
• Year: 2011
• Where: ICCV
• Authors: Richard A. Newcombe, Steven Lovegrove, Andrew J. Davison
• Keywords: Computer Vision, Depth Maps, ICCV 2011, Image Alignment, Real Time Camera