3 ms·
Lossily compress the point cloud then, come on. For thin two-sided objects like laptops, rasterize the depth map of each side. You might be interested in how b
by gcr 4y ago
Lossily compress the point cloud then, come on. For thin two-sided objects like laptops, rasterize the depth map of each side.
You might be interested in how biometric hashes for things like fingerprints or irises work, since these have the same problems: the biometric is decomposed into a “stable” part and an “unstable” part. The stable part is hashed and the unstable part is encoded as a residual. W.J.Scheirer and T.E.Boult’s work on bipartite biotokens is one potential implementation
- nonrandomstring 4y ago> W.J.Scheirer and T.E.Boult's work on bipartite biotokens is one potential implementation Cheers. Something maybe like that already going on with a bespoke principal component analysis. But finding the needle in the haystack is knowing what _might_ change and be significant. Perhaps someone re-flashes a EEPROM, leaving only tiny dimple in a gold PCB pad. A system sensitive enough to pick that up doesn't necessarily know that a micro-fracture caused by vibration isn't a threat. What you're suggesting might be good for image processing of the plastic bead vacuum shield though.