Real time object scanning using a mobile phone and cloud-based visual search engine

1. A system, comprising:

an interface configured to receive, via a network, an image generated by a camera of a mobile device;

a memory; and

a processor, at least one of the processor or the memory being configured to:

determine a key frame of the image, wherein determining a key frame comprises determining that the image is stable;

determine a tag for an item in the key frame based, at least in part, upon the tag being received from one or more human taggers;

determine a validity of the tag received from the one or more human taggers based, at least in part, upon a status of the one or more human taggers from which the tag was received; and

providing tagging results to the mobile device in real time based, at least in part, on the validity of the tag received from the one or more human taggers;

wherein a plurality of human taggers including the human taggers are divided into separate groups according to one or more characteristics including their average time of providing tags.

2. A system as in claim 1 , wherein determining that the image is stable comprises determining that at least a particular number of a plurality of features of the image remain that have not moved more than a threshold.

3. A system as in claim 2 , wherein a percentage of the plurality of features is above a threshold for a predetermined number of frames.

4. A system as in claim 2 , wherein a number of the plurality of features is above a threshold for a predetermined number of frames.

5. A system as in claim 2 , wherein each of the plurality of features is in a current frame and a prior frame.

6. A system as in claim 1 , at least one of the processor or the memory being configured to:

determine movement associated with a plurality of features of the image;

in the event that a specific feature of the plurality of features has movement above a threshold, remove the specific feature from the plurality of features such that a reduced set of features is generated;

determine a tag for an item in the key frame based, at least in part, upon at least a portion of the reduced set of features;

wherein the specific feature is in the current frame and in a prior frame.

7. A system as in claim 1 , wherein the mobile device comprises a mobile phone.

8. A system as in claim 1 , wherein the mobile device comprises a tablet.

9. A system as in claim 1 , wherein the key frame has visual content different from visual content from a previous key frame.

10. A system as in claim 1 , the human taggers being associated with a particular specialty, wherein the status of each of the human taggers indicates whether the human tagger is an expert.

11. A system as in claim 1 , wherein the one or more human taggers have a common set of characteristics including a particular location.

12. A computer-implemented method, comprising:

receiving, via a network, an image from a mobile device;

determining, by a processor, a key frame of the image, wherein determining a key frame comprises determining that an image is stable;

determining a tag for an item in the key frame based, at least in part, upon the tag being received from one or more human taggers;

determining a validity of the tag received from the one or more human taggers based, at least in part, upon a status of the one or more human taggers from which the tag was received; and

providing tagging results to the mobile device in real time based, at least in part, on the validity of the tag received from the one or more human taggers;

wherein the one or more human taggers share a common set of characteristics, the common set of characteristics including a particular average time to provide results;

wherein a plurality of human taggers including the human taggers are divided into separate groups according to one or more characteristics including their average time of providing tags.

13. A computer-implemented method as in claim 12 , wherein the tag is determined using a human computation module configured to communicate with the one or more human taggers.

14. A computer-implemented method as in claim 13 , further comprising:

requesting, by the human computation module, the tag from the one or more human taggers.

15. A computer-implemented method as in claim 14 , wherein the one or more human taggers have a common set of characteristics, the common set of characteristics including at least one of a location or specialty.

16. A computer-implemented method as in claim 13 , wherein the tag is determined using the human computation module after determining that the tag could not be determined using a computer vision module.

17. A computer-implemented method as in claim 12 , wherein the status of each of the human taggers indicates whether the human tagger is a reliable tagger.

18. A computer-implemented method as in claim 12 , the human taggers being associated with a particular specialty, wherein the status of each of the human taggers indicates whether the human tagger is an expert.

19. A computer-implemented method as in claim 12 , further comprising:

marking the tag received from the one or more human taggers with a validity status based on the status of the one or more human taggers.

20. A computer-implemented method as in claim 12 , wherein the tag is provided for display via the mobile device.

21. The method as recited in claim 12 , wherein the common set of characteristics comprise a particular location and a particular specialty.

22. A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:

receiving, via a network, an image from a mobile device;

determining, by a processor, a key frame of the image, wherein determining a key frame comprises determining that an image is stable;

determining a tag for an item in the key frame based, at least in part, upon the tag being received from one or more human taggers;

determining a validity of the tag received from the one or more human taggers based, at least in part, upon a status of the one or more human taggers from which the tag was received; and

providing tagging results to the mobile device in real time based, at least in part, on the validity of the tag received from the one or more human taggers;

wherein a plurality of human taggers including the human taggers are divided into separate groups according to one or more characteristics including their average time of providing tags.

23. A computer program product as in claim 22 , wherein the image is stable if the image has been still for at least a predetermined number of frames.

24. A computer program product as in claim 22 , further comprising:

determining whether to add the image to an object database in association with the tag; and

storing the image in the object database in association with the tag according to a result of determining whether to add the image to the object database in association with the tag.

25. A computer program product as in claim 22 , further comprising instructions for:

extracting features at object contours of the image;

removing features from the extracted features that are above a blurriness threshold such that a reduced set of features is generated; and

determining a tag for an item in the key frame based, at least in part, upon at least a portion of the reduced set of features.