| ▲ | joshvm 3 days ago | |
Yes, I've worked in this space for dogs (for re-identifying animals that have been vaccinated for rabies). It's a very difficult problem, but mostly because getting/scraping good training data is difficult. You really want lots of paired images of the same animal and that's hard compared to searching for "cat". Plus the usual challenges: animals don't like to stay still so getting good pictures is hard and users must have good guidance for lighting/pose to get the best results. Human facial recognition benefits from strong commercial interest and the most robust methods rely on extras like 3D scanning. Tricks include facial alignment + cropping and very strong constraints on orientation to make sure you have a good frontal image (apps will give users photo alignment markers). Otherwise it's a standard visual seatch. Run a face extraction model to get the crop, warp to standard key points, compute the crop embedding, store in a database and do a nearest neighbour lookup. There are a few startups doing this. Also look at PetFace which was a benchmark released a year or so ago. Not a huge amount of work in this area compared to humans, but it's of interest to people like cattle farmers as well. | ||