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1. (WO2019046078) DÉTECTION DE FAUX POSITIFS DANS LA RECONNAISSANCE FACIALE
Note: Texte fondé sur des processus automatiques de reconnaissance optique de caractères. Seule la version PDF a une valeur juridique

CLAIMS

WHAT IS CLAIMED IS:

1. A method of detecting false positive faces in one or more video frames, the method comprising:

obtaining a video frame of a scene, the video frame including a face of a user associated with at least one characteristic feature;

determining the face of the user matches a representative face from stored representative data, the representative face being associated with the at least one characteristic feature, wherein the face of the user is determined to match the representative face based on the at least one characteristic feature; and

determining the face of the user is a false positive face based on the face of the user matching the representative face.

2. The method of claim 1, further comprising:

accessing the representative data, the representative data including information representing features of a plurality of representative faces associated with different versions of at least one characteristic feature;

accessing registration data, the registration data including information representing features of a plurality of registered faces; and

comparing information representing features of the face of the user with the information representing the features of the plurality of representative faces and with the information representing the features of the plurality of registered faces;

wherein the face of the user is determined to match the representative face and determined to be a false positive face based on the comparison.

3. The method of claim 2, wherein the information representing the features of the plurality of faces from the representative data includes a plurality of representative feature vectors for the plurality of faces.

4. The method of claim 2, wherein comparing the information representing the features of the face of the user with the information representing the features of the plurality of registered faces is performed without using the at least one representative feature.

5. The method of claim 1, wherein determining the face of the user matches the representative face from the representative data includes:

comparing information representing features of the face of the user with information representing features of a plurality of representative faces from the representative data and with information representing features of a plurality of registered faces from registration data; and determining the face from the representative data is a closest match with the face of the user based on the comparison.

6. The method of claim 5, wherein the information representing features of the face of the user is determined by extracting features of the face from the video frame.

7. The method of claim 1, wherein the at least one characteristic feature includes glasses, and wherein different versions of the at least one characteristic feature includes different types of glasses.

8. The method of claim 1, wherein the at least one characteristic feature includes facial hair, and wherein different versions of the at least one characteristic feature includes different types of facial hair.

9. The method of claim 1, further comprising generating the representative data, wherein generating the representative data comprises:

obtaining a set of representative images, each representative image including a face from a plurality of faces associated with different versions of the at least one characteristic feature; generating a plurality of feature vectors for the plurality of faces;

clustering the plurality of feature vectors using data clustering to determine a plurality of cluster groups;

determining, for a cluster group from the plurality of cluster groups, a representative feature vector from the plurality of feature vectors, the representative feature vector being closest to a mean of the cluster; and

adding the representative feature vector to the representative data, the representative feature vector representing a representative face from a plurality of representative faces in the representative data.

10. The method of claim 9, further comprising:

extracting one or more local features of each face from the plurality of faces; and generating the plurality of feature vectors for the plurality of faces using the extracted one or more local features.

11. The method of claim 10, further comprising:

dividing the one or more local features into a plurality of feature groups; and

wherein generating the plurality of feature vectors includes generating a feature vector for each feature group of the plurality of feature groups.

12. An apparatus for detecting false positive faces in one or more video frames, comprising:

a memory configured to store video data associated with the video frames; and a processor configured to:

obtain a video frame of a scene, the video frame including a face of a user associated with at least one characteristic feature;

determine the face of the user matches a representative face from stored representative data, the representative face being associated with the at least one characteristic feature, wherein the face of the user is determined to match the representative face based on the at least one characteristic feature; and

determine the face of the user is a false positive face based on the face of the user matching the representative face.

13. The apparatus of claim 12, wherein the processor is configured to:

access the representative data, the representative data including information representing features of a plurality of representative faces associated with different versions of at least one characteristic feature;

access registration data, the registration data including information representing features of a plurality of registered faces; and

compare information representing features of the face of the user with the information representing the features of the plurality of representative faces and with the information representing the features of the plurality of registered faces;

wherein the face of the user is determined to match the representative face and determined be a false positive face based on the comparison.

14. The apparatus of claim 13, wherein the information representing the features of the plurality of faces from the representative data includes a plurality of representative feature vectors for the plurality of faces.

15. The apparatus of claim 13, wherein comparing the information representing the features of the face of the user with the information representing the features of the plurality of registered faces is performed without using the at least one representative feature.

16. The apparatus of claim 12, wherein determining the face of the user matches the representative face from the representative data includes:

comparing information representing features of the face of the user with information representing features of a plurality of representative faces from the representative data and with information representing features of a plurality of registered faces from registration data; and determining the face from the representative data is a closest match with the face of the user based on the comparison.

17. The apparatus of claim 16, wherein the information representing features of the face of the user is determined by extracting features of the face from the video frame.

18. The apparatus of claim 12, wherein the at least one characteristic feature includes glasses, and wherein different versions of the at least one characteristic feature includes different types of glasses.

19. The apparatus of claim 12, wherein the at least one characteristic feature includes facial hair, and wherein different versions of the at least one characteristic feature includes different types of facial hair.

20. The apparatus of claim 12, wherein the processor is configured to generate the representative data, wherein generating the representative data comprises:

obtaining a set of representative images, each representative image including a face from a plurality of faces associated with different versions of the at least one characteristic feature; generating a plurality of feature vectors for the plurality of faces;

clustering the plurality of feature vectors using data clustering to determine a plurality of cluster groups;

determining, for a cluster group from the plurality of cluster groups, a representative feature vector from the plurality of feature vectors, the representative feature vector being closest to a mean of the cluster; and

adding the representative feature vector to the representative data, the representative feature vector representing a representative face from a plurality of representative faces in the representative data.

21. The apparatus of claim 20, wherein the processor is configured to:

extract one or more local features of each face from the plurality of faces; and

generate the plurality of feature vectors for the plurality of faces using the extracted one or more local features.

22. The apparatus of claim 21, wherein the processor is configured to:

divide the one or more local features into a plurality of feature groups; and

wherein generating the plurality of feature vectors includes generating a feature vector for each feature group of the plurality of feature groups.

23. The apparatus of claim 12, wherein the apparatus comprises a mobile device.

24. The apparatus of claim 23, further comprising one or more of:

a camera for capturing the one or more video frames; and

a display for displaying the one or more video frames.

25. A non-transitory computer-readable medium having stored thereon instructions that, when executed by one or more processors, cause the one or more processor to:

obtain a video frame of a scene, the video frame including a face of a user associated with at least one characteristic feature;

determine the face of the user matches a representative face from stored representative data, the representative face being associated with the at least one characteristic feature, wherein the face of the user is determined to match the representative face based on the at least one characteristic feature; and

determine the face of the user is a false positive face based on the face of the user matching the representative face.

26. The non-transitory computer-readable medium of claim 25, further comprising instructions that, when executed by one or more processors, cause the one or more processor to: access the representative data, the representative data including information representing features of a plurality of representative faces associated with different versions of at least one characteristic feature;

access registration data, the registration data including information representing features of a plurality of registered faces; and

compare information representing features of the face of the user with the information representing the features of the plurality of representative faces and with the information representing the features of the plurality of registered faces;

wherein the face of the user is determined to match the representative face and determined be a false positive face based on the comparison.

27. The non-transitory computer-readable medium of claim 25, wherein determining the face of the user matches the representative face from the representative data includes:

comparing information representing features of the face of the user with information representing features of a plurality of representative faces from the representative data and with information representing features of a plurality of registered faces from registration data; and determining the face from the representative data is a closest match with the face of the user based on the comparison.

28. The non-transitory computer-readable medium of claim 25, wherein the at least one characteristic feature includes glasses, and wherein different versions of the at least one characteristic feature includes different types of glasses.

29. The non-transitory computer-readable medium of claim 25, wherein the at least one characteristic feature includes facial hair, and wherein different versions of the at least one characteristic feature includes different types of facial hair.

30. The non-transitory computer-readable medium of claim 25, further comprising instructions that, when executed by one or more processors, cause the one or more processor to generate the representative data, wherein generating the representative data comprises:

obtaining a set of representative images, each representative image including a face from a plurality of faces associated with different versions of the at least one characteristic feature; generating a plurality of feature vectors for the plurality of faces;

clustering the plurality of feature vectors using data clustering to determine a plurality of cluster groups;

determining, for a cluster group from the plurality of cluster groups, a representative feature vector from the plurality of feature vectors, the representative feature vector being closest to a mean of the cluster; and

adding the representative feature vector to the representative data, the representative feature vector representing a representative face from a plurality of representative faces in the representative data.