Our paper, “MONORAIL: A Disk-Friendly Index for Huge Descriptor Databases” was accepted at the upcoming IAPR Internation Conference on Pattern Recognition — ICPR 2010. Here is the abstract:
We propose MONORAIL, an indexing scheme for very large multimedia descriptor databases. Our index is based on the Hilbert curve, which is able to map the high-dimensional space of those descriptors to a single dimension. Instead of using several curves to mitigate boundary effects, we use a single curve with several surrogate points for each descriptor. Thus, we are able to reduce the random accesses to the bare minimum. In a rigorous empirical comparison with another method based on multiple surrogates, ours shows a significant improvement, due to our careful choice of the surrogate points.
I am particularly proud of this paper, not only because of the method itself, but also because of the experimental design we propose for the validation. I have been studying for more than a year the topics of Design of Experiments, statistical tests and validation. This is the first of a crop of publications that are employing those rigorous evaluation tools, which, though commonplace in other fields, are still seldom used in Computer Sciences.