Dynamic Optimal Path Selection for 3D Triangulation with Multiple Cameras

When a physical feature is observed by two or more cameras, its position in the 3D space can be easily recovered by means of triangulation. However, for such estimate to be reliable, accurate intrinsic and extrinsic calibration of the capturing devices must be available. Extrinsic parameters are usually the most problematic, especially when dealing with a large number of cameras. This is due to several factors, including the inability to observe the same reference object over the entire network and the sometimes unavoidable displacement of cameras over time. With this paper we propose a game-theoretical method that can be used to dynamically select the most reliable rigid motion between cameras observing the same feature point. To this end we only assume to have a (possibly incomplete) graph connecting cameras whose edges are labelled with extrinsic parameters obtained through pairwise calibration.When a physical feature is observed by two or more cameras, its position in the 3D space can be easily recovered by means of triangulation. However, for such estimate to be reliable, accurate intrinsic and extrinsic calibration of the capturing devices must be available. Extrinsic parameters are usually the most problematic, especially when dealing with a large number of cameras. This is due to several factors, including the inability to observe the same reference object over the entire network and the sometimes unavoidable displacement of cameras over time. With this paper we propose a game-theoretical method that can be used to dynamically select the most reliable rigid motion between cameras observing the same feature point. To this end we only assume to have a (possibly incomplete) graph connecting cameras whose edges are labelled with extrinsic parameters obtained through pairwise calibration