Thursday, February 23rd, 2012, 9:59 pm
Further Validation With GMDS
RECENTLY uploaded a report exceeding 500 pages. The report has been narrowed down to include some of the better results that we have and some of the more important points worth getting across. A lot of the text is new and a lot in the content and organisation can be improved given more time. This too will be uploaded soon.
I’ve been running further experiments while the report was being worked on (still work in progress) and some interesting results were reached when particularly fast configurations of the GMDS algorithm were attempted, giving (so far) perfect classification for 30 pairs.
Previously, in experiments shown in the report, verification performance reached through GMDS was limited and primarily impeded not only by failures at the topology level but also finer-level issues where the 3-D surfaces provided not enough information to correctly distinguish between identities. A lot of the topological failures were averted by further optimising the algorithm such that support is made broader.
The first ROC curve shows the performance where only GMDS is used and the mask omits much of the cheeks, whereas the latter mostly includes them. By altering the configurations to the best we’ve found so far, significantly better performance can be assured (with GMDS and 3-D alone), but it would be nowhere near the accuracy levels we compete against. Cross-individual entropy seems to lie somewhere in the combination of many 3-D features, but accurate segmentation is not easy on smooth surfaces.