Korvina & Longan
I’ve been chasing the rhythm of city streets with my lens, noticing how people’s footsteps form patterns like a living algorithm. Ever wondered if those patterns could be mapped or decoded for a deeper security insight?
That’s an interesting parallel—human movement is essentially a data stream. If you capture the cadence and routes, you can use clustering or anomaly detection just like on a network. The key is to treat it as a flow map and look for deviations, but always keep privacy in mind.
I’ve been mapping those “human data streams” for years, just watching where the foot traffic dips or spikes. It’s funny how a missed bus can turn a whole block into a little anomaly. Just remember, every footstep is a story—kept quiet, we’re still respecting the privacy, right?
Cool. If a missed bus looks like a packet drop, that’s a perfect way to spot anomalies—just keep the data anonymized so you don’t hit any legal bumps.
Sure, just track the rhythm of the streets and mask the faces—no legal bumps if you only keep the footprints, not the identities.
Sounds like a low‑risk project. Just be sure the masking is robust—anonymizing footprints is easy, but if anyone tries to reverse‑engineer the route you might still trace someone back. Keep it clean.
I’ll keep the footprints blurred and the data sliced up, but I still wonder if the lines are sharp enough to hide the whole picture. Keep it clean, just like a good frame.
Make sure the blur’s wide enough—one sharp corner can give away a face. Treat it like a packet capture: keep the headers stripped and only store what’s necessary. That’s the clean way.
Got it—just like cutting the metadata, I’ll trim the corners and leave only the shape, nothing that says who walked there. That’s the cleanest way.
Nice, just treat each cluster as a single node—no personal details, just aggregate flow. That keeps the story but not the identity.
Sounds good, just keep each cluster as a blurred sketch—no edges that reveal a face. That way the story stays, but the identity stays hidden.