1. A computer-implemented method, comprising:
performing face detection, using a processor, on a plurality of images to identify a plurality of faces;
activating a subset of the plurality of faces, including by loading data associated with the subset of faces into a processing memory, wherein at least one of the plurality of faces is un-activated, including by keeping data associated with the at least one of the plurality of faces out of the processing memory;
calculating a distance for each pair of activated faces, wherein the distance is associated with a measure of a similarity between a first face and a second face;
clustering the activated faces into a plurality of groups based at least in part on the distances;
reducing an amount of information loaded in the processing memory, including by modifying data associated with at least one of the plurality of groups; and
after reducing, activating at least one un-activated face, including by loading data associated with the at least one un-activated face into the processing memory.
2. The method of claim 1, where activating the subset is initiated when face detection has completed for one or more of the following: a predefined number of images or for a predefined number of faces.
3. The method of claim 1, wherein activating the subset is based at least in part on one or more of the following: whether another face in the same image is activated, whether another face having a similar timestamp is activated, whether an image is selected by a user, or if a face has better quality information than another face.
4. The method of claim 1, wherein activating the subset includes activating a predefined number of faces.
5. The method of claim 1, wherein calculating the distance includes: in the event a first face is associated with a first label and a second face is associated with a second label, which is different from the first label, setting a distance between the first face and the second face to one or more of the following: an infinite value or a maximum value.
6. The method of claim 1, wherein calculating the distance includes: in the event a first face and a second face are associated with a same image, setting a distance between the first face and the second face to one or more of the following: an infinite value or a maximum value.
7. The method of claim 1 further comprising receiving at least one label in response to displaying.
8. The method of claim 7 further comprising displaying an unlabeled face with a suggested label.
9. The method of claim 7 further comprising reducing an amount of information associated with a first face and a second face that are assigned a same label.
10. The method of claim 9, wherein reducing the amount of information includes generating composite information based at least in part on information associated with the first face and information associated with the second face.
11. The method of claim 9, wherein reducing the amount of information includes:
selecting either information associated with the first face or information associated with the second face;
retaining the selected information; and
discarding the unselected information.
12. A system, comprising:
a processor; and
a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to:
perform face recognition processing on a plurality of images to identify a plurality of faces;
activate a subset of the plurality of faces, including by loading data associated with the subset of faces into a processing memory, wherein at least one of the plurality of faces is un-activated, including by keeping data associated with the at least one of the plurality of faces out of the processing memory;
calculate a distance for each pair of activated faces, wherein the distance is associated with a measure of a similarity between a first face and a second face;
cluster the activated faces into a plurality of groups based at least in part on the distances;
reduce an amount of information loaded in the processing memory, including by modifying data associated with at least one of the plurality of groups; and
after reducing, activate at least one un-activated face, including by loading data associated with the at least one un-activated face into the processing memory.
13. The system of claim 12, wherein activating is based at least in part on one or more of the following: whether another face in the same image is activated, whether another face having a similar timestamp is activated, whether an image is selected by a user, or if a face has better quality information than another face.
14. The system of claim 12, wherein the instructions for calculating the distance include instructions for: in the event a first face is associated with a first label and a second face is associated with a second label which is different from the first label, setting a distance between the first face and the second face to one or more of the following: an infinite value or a maximum value.
15. The system of claim 12, wherein the instructions for calculating the distance include instructions for: in the event a first face and a second face are associated with a same image, setting a distance between the first face and the second face to one or more of the following: an infinite value or a maximum value.
16. A computer program product the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
performing face recognition processing, on a plurality of images to identify a plurality of faces;
activating a subset of the plurality of faces, including by loading data associated with the subset of faces into a processing memory, wherein at least one of the plurality of faces is un-activated, including by keeping data associated with the at least one of the plurality of faces out of the processing memory;
calculating a distance for each pair of activated faces, wherein the distance is associated with a measure of a similarity between a first face and a second face;
clustering the activated faces into a plurality of groups based at least in part on the distances;
reducing an amount of information loaded in the processing memory, including by modifying data associated with at least one of the plurality of groups; and
after reducing, activating at least one un-activated face, including by loading data associated with the at least one un-activated face into the processing memory.
17. The computer program product of claim 16 further comprising computer program instructions for:
receiving at least one label in response to displaying; and
reducing an amount of information associated with a first face and a second face that are assigned a same label.
18. The computer program product of claim 17, wherein reducing the amount of information includes:
selecting either information associated with the first face or information associated with the second face;
retaining the selected information; and
discarding the unselected information.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. Non-slip footwear comprising:
a main body formed of a flexible material and formed to surround the sole of a foot of a user and to open the top side of the foot;
toe insertion holes formed of the flexible material, protruding from the front part of the main body so that toes of the foot are respectively inserted into the toe insertion holes;
an non-slip outsole formed at the heel part of the main body and formed of foamed rubber having abrasion resistance, and having a thickness of 1 mm\u02dc5 mm; and
non-slip dots formed at the sole part of the main body and the non-slip outsole (30).
2. The non-slip footwear according to claim 1, wherein the flexible material is a synthetic fiber having flexibility.
3. The non-slip footwear according to claim 1, wherein acupressure protrusions protrude from the inner surface of the main body.
4. The non-slip footwear according to claim 1, wherein the front parts of the toe insertion holes are opened so that the front parts of the toes protrude outward from the non-slip footwear.
5. The non-slip footwear according to claim 1, wherein toe corrective inserts formed of silicon and having elasticity and shape stability are formed at areas between the toes of the toe insertion holes.
6. The non-slip footwear according to claim 1, wherein bending parts having elasticity are formed at the end of the top part of the main body and the ends of the front parts of the toe insertion holes.
7. The non-slip footwear according to claim 2, wherein acupressure protrusions protrude from the inner surface of the main body.
8. The non-slip footwear according to claim 2, wherein the front parts of the toe insertion holes are opened so that the front parts of the toes protrude outward from the non-slip footwear.
9. The non-slip footwear according to claim 2, wherein toe corrective inserts formed of silicon and having elasticity and shape stability are formed at areas between the toes of the toe insertion holes.
10. The non-slip footwear according to claim 4, wherein toe corrective inserts formed of silicon and having elasticity and shape stability are formed at areas between the toes of the toe insertion holes.
11. The non-slip footwear according to claim 2, wherein bending parts having elasticity are formed at the end of the top part of the main body and the ends of the front parts of the toe insertion holes.