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Which spatial search structure for bounding boxes?

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my data is about 70.000 objects (so called fibers where each fiber is essentially a line strip) in R^3. I want to compute a relation between each pair of fibers, but I don't have to compute if they are not close to each other. But if they are very distant to each other this relation will always equal to zero.

To speed up, I thought I could generate bounding boxes (axis parallel), and make use of a spatial search structure, to quickly identify if the both boxes are close or distant to each other. When googeling I lost the overview over kd-Trees, Bounding Interval Hierarchies, Bounding Volume Hierarchies, Oct-Tree,...

Sorry, can someone advise me what to use? And I would also be interested in literature on the spatial search structure topic. Computational geometry books does not seem to cover this area very well, they just use sometimes those data structures.

Ah and finally I would be interested in a free implementation in C++.

Thank you very much

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