Locally Planar Patch Features for Real-Time Structure from Motion

The performance of sequential structure from motion systems, where scene mapping is sparse to permit real-time operation, depends greatly on the ability to repeatedly measure the same visual features from a wide range of viewpoints. While previous systems have tracked features as 2D templates in image space, we show that long-term tracking is improved by treating salient feature patches as observations of locally planar regions on 3D world surfaces. Within a SLAM framework for motion and structure estimation, a gradient-based image alignment method is used to deduce estimates feature surface normal estimates, enabling pre-warping of templates for matching. As an added benet these normals provide a richer description of the scene.