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GEA optimization for live structureless motion estimation

In this paper we describe a highly efficient and scalable real-time camera motion estimation system. Instead of Bundle Adjustment, this system uses Global Epipolar Adjustment (GEA) [11] to correct bootstrapping and loop-closing errors during the camera tracking process. We propose a modification of the GEA algorithm to obtain a significant speed-up in the optimization, without sacrificing loop-closing error correction performance. As a result, our motion estimation system features increased performance and scalability. In addition, it can perform long-term live motion estimation without explicitly maintaining the whole 3D structure. The system stores only the 3D location for the most recently detected features, to resect the camera pose for new input frames.