Generalized Detection and Merging of Loop Closures for Video Sequences
Manfred Klopschitz, Christopher Zach, Arnold Irschara, Dieter Schmalstieg · 2008
In this work we present a method to detect overlaps in image sequences, and use this information to integrate overlapping sparse 3D structure from video sequences. The additional temporal information of these images is used to increase robustness over single image pair matching. A scanline optimization problem formulation is used to compute the best sequence alignment using wide-baseline image matching techniques. Compared to a direct dynamic programming approach, the scanline optimization formulation increases the robustness of sequence alignment for general relative motions. The proposed alignment method is employed to integrate sparse 3D models reconstructed from separate video sequences. In addition loop closures are detected. Consequently, the 3D modeling process from sequential image data can be split into fast sequence processing and subsequent global integration steps. 1.