Real-time image-based 6-DOF localization in large-scale environments

We present a real-time approach for image-based localization within large scenes that have been reconstructed offline using structure from motion (Sfm). From monocular video, our method continuously computes a precise 6DOF camera pose, by efficiently tracking natural features and matching them to 3D points in the Sfm point cloud. Our main contribution lies in efficiently interleaving a fast keypoint tracker that uses inexpensive binary feature descriptors with a new approach for direct 2D-to-3D matching. The 2D-to-3D matching avoids the need for online extraction of scale-invariant features. Instead, offline we construct an indexed database containing multiple DAISY descriptors per 3D point extracted at multiple scales. The key to the efficiency of our method lies in invoking DAISY descriptor extraction and matching sparingly during localization, and in distributing this computation over a window of successive frames. This enables the algorithm to run in real-time, without fluct...

• Type: Journal
• Year: 2012
• Where: CVPR
• Authors: Hyon Lim, Sudipta N. Sinha, Michael F. Cohen, Matthew Uyttendaele
• Keywords: Computer Vision, Cvpr 2012, Invariant Features, Micro Aerial Vehicle, Point Cloud