4 ms·

It would, perhaps, but the problem is deciding between millions (or billions) of people -- if you recognize people by doing pair-wise comparisons, then even sma

by apu 13y ago

It would, perhaps, but the problem is deciding between millions (or billions) of people -- if you recognize people by doing pair-wise comparisons, then even small error rates can quickly add up.

seiji 13y ago
All you have to do is turn people into a feature vector then KNN them. Perhaps once you're in a smaller neighborhood, you can do more intensive analysis for high probability equality matching.
- apu 13y ago
  This is not going to work (at least currently). Features for faces are not yet powerful enough to get you to a reasonable set of matches without also missing the right face in a large percentage of cases. Variations due to lighting, pose, and expression end up causing the same person to look very different -- often to the point where two different people in the same configuration can look more similar than the same person in different configurations. That being said, if the database is small enough (e.g., in a limited scenario or by applying other non-vision filters first), then the state of the art methods do use a similar approach. However, in practice people use methods with much stronger priors than KNN. Because faces fall into a low-dimensional manifold[1], you can take advantage of that to constrain queries much more than with generic KNN. [1] My PhD advisor has published several works about this topic, e.g., http://vision.ucsd.edu/kriegman-grp/papers/ijcv98.pdf http://vision.ucsd.edu/kriegman-grp/papers/ijcv98.pdf http://virtualhost.cs.columbia.edu/~belhumeur/journal/invariance_v2.pdf http://virtualhost.cs.columbia.edu/~belhumeur/journal/invari... http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.3344&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123...
angersock 13y ago
If only we had some social context information available to differentiate the three other faces that look like mine... ...oh wait. Fuck. :(
Irishsteve 13y ago
Stick in some geo information as well (If you are trying to identify Mr X at location Y). That might work ?
- apu 13y ago
  Yes, as the story points out, searching the entire database for a face probably won't work, but if you can prefilter based on other criteria such as location, employer, etc., it might become more feasible.

by apu 13y ago

It would, perhaps, but the problem is deciding between millions (or billions) of people -- if you recognize people by doing pair-wise comparisons, then even small error rates can quickly add up.

seiji 13y ago

All you have to do is turn people into a feature vector then KNN them. Perhaps once you're in a smaller neighborhood, you can do more intensive analysis for high probability equality matching.

apu 13y ago
This is not going to work (at least currently). Features for faces are not yet powerful enough to get you to a reasonable set of matches without also missing the right face in a large percentage of cases. Variations due to lighting, pose, and expression end up causing the same person to look very different -- often to the point where two different people in the same configuration can look more similar than the same person in different configurations. That being said, if the database is small enough (e.g., in a limited scenario or by applying other non-vision filters first), then the state of the art methods do use a similar approach. However, in practice people use methods with much stronger priors than KNN. Because faces fall into a low-dimensional manifold[1], you can take advantage of that to constrain queries much more than with generic KNN. [1] My PhD advisor has published several works about this topic, e.g., http://vision.ucsd.edu/kriegman-grp/papers/ijcv98.pdf http://vision.ucsd.edu/kriegman-grp/papers/ijcv98.pdf http://virtualhost.cs.columbia.edu/~belhumeur/journal/invariance_v2.pdf http://virtualhost.cs.columbia.edu/~belhumeur/journal/invari... http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.3344&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123...

angersock 13y ago

If only we had some social context information available to differentiate the three other faces that look like mine... ...oh wait. Fuck. :(

Irishsteve 13y ago

Stick in some geo information as well (If you are trying to identify Mr X at location Y). That might work ?

apu 13y ago
Yes, as the story points out, searching the entire database for a face probably won't work, but if you can prefilter based on other criteria such as location, employer, etc., it might become more feasible.