SCALE INVERIANT OBJECT DETECTION

• US 20200311463A1
• Filed: 08/28/2019
• Published: 10/01/2020
• Est. Priority Date: 03/31/2019
• Status: Active Grant

• Current Assignee: Cortica Ltd.
• Original Assignee: Cortica Ltd.
• Inventors: Raichelgauz, Igal, Odinaev, Karina
• Granted Patent: US 10,846,570 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/211 Selection of the most significant subset of features
• CPC Class Codes: G06F 18/2155 characterised by the incorporation of unlabelled data, e.g. multiple instance learning [MIL], semi-supervised techniques using expectation-maximisation [EM] or naïve labelling
• CPC Class Codes: G06F 18/217 Validation; Performance evaluation; Active pattern learning techniques
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 18/25 Fusion techniques
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/20221 Image fusion; Image merging
• CPC Class Codes: G06T 3/40 Scaling of whole images or parts thereof, e.g. expanding or contracting
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 10/422 for representing the structure of the pattern or shape of an object therefor
• CPC Class Codes: G06V 10/454 Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44
• CPC Class Codes: G06V 20/46 Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames

Abstract

Systems, and method and computer readable media that store instructions for scale invariant object detection.

Claims

1. A method for scale invariant object detection, the method comprises:

receiving or generating a first image in which an object appears in a first scale and a second image in which the object appears in a second scale that differs from the first scale;

generating a first image signature and a second image signature;

wherein the first image signature comprises a first group of at least one certain first image identifier that identifies at least a part of the object;

wherein the second image signature comprises a second group of certain second image identifiers that identify different parts of the object;

wherein the second group is larger than th first group; and

linking between the at least one certain first image identifier and the certain second image identifiers.

2. The method according to claim 1 comprising linking between the first image signature, the second image signature and the object.

3. The method according to claim 1 wherein the linking comprises adding the first signature and the second signature to a certain concept structure that is associated with the object.

4. The method according to claim 3 comprising:

receiving or generating an input image;

generating a signature of the input image;

comparing the signature of the input image to signatures of the certain concept structure; and

determining that the input image comprises the object when at least one of the signatures of the certain concept structure matches the signature of the input image.

5. The method according to claim 1 comprising:

receiving or generating an input image;

generating a signature of the input image, the signature of the input image comprises only some of the certain second image identifiers;

wherein the input image is of the second scale;

changing a scale of the input image to the first scale to a provide an amended input image;

generating a signature of the amended input image; and

verifying that the input image comprises the object when the signature of the amended input image comprises the at least one certain first image identifier.

6. The method according to claim 1 comprising:

receiving or generating an input image;

generating a signature of the input image;

searching in the signature of the input image for at least one of (a) the at least one certain first image identifier, and (b) the certain second image identifiers; and

determining that the input image comprises the object when the signature of the input image comprises the at least one of (a) the at least one certain first image identifier, and (b) the certain second image identifiers.

7. The method according to claim 1 comprising:

receiving or generating an input image;

generating a signature of the input image;

searching in the signature of the input image for at least one of (a) one or more certain first image identifier of the at least one certain first image identifier, and (b) at least one certain second image identifier of the certain second image identifiers; and

determining that the input image includes the object when the signature of the input image comprises the at least one of (a) one or more certain first image identifier of the at least one certain first image identifier, and (b) the at least one certain second image identifier.

28. The method according to claim 1 wherein each one of the at least one certain first image identifier differs from each one of the certain second image identifiers.

29. The method according to claim 1 wherein each one of the at least one certain first image identifier is not similar to each one of the certain second image identifiers.

8. A non-transitory computer readable medium for scale invariant object detection, the non-transitory computer readable medium stores instructions for:

receiving or generating a first image in which an object appears in a first scale and a second image in which the object appears in a second scale that differs from the first scale;

generating a first image signature and a second image signature;

wherein the first image signature comprises a first group of at least one certain first image identifier that identifies at least a part of the object;

wherein the second image signature comprises a second group of certain second image identifiers that identify different parts of the object;

wherein the second group is larger than the first group; and

linking between the at least one certain first image identifier and the certain second image identifiers.

9. The non-transitory computer readable medium according to claim 8 that stores instructions for linking between the first image signature, the second image signature and the object.

10. The non-transitory computer readable medium according to claim 8 wherein the linking comprises adding the first signature and the second signature to a certain concept structure that is associated with the object.

11. The non-transitory computer readable medium according to claim 10 that stores instructions for:

receiving or generating an input image;

generating a signature of the input image;

comparing the signature of the input image to signatures of the certain concept structure; and

determining that the input image comprises the object when at least one of the signatures of the certain concept structure matches the signature of the input image.

12. The non-transitory computer readable medium according to claim 8 that stores instructions for:

receiving or generating an input image;

generating a signature of the input image, the signature of the input image comprises only some of the certain second image identifiers;

wherein the input image is of the second scale;

changing a scale of the input image to the first scale to provide an amended input image;

generating a signature of the amended input image; and

verifying that the input image comprises the object when the signature of the amended input image comprises the at least one certain first image identifier.

13. The non-transitory computer readable medium according to claim 8 that stores instructions for:

receiving or generating an input image;

generating a signature of the input image;

searching in the signature of the input image for at least one of (a) the at least one certain first image identifier, and (b) the certain second image identifiers; and

determining that the input image includes the object when the signature of the input image comprises the at least one of (a) the at least one certain first image identifier, and (b) the certain second image identifiers.

14. The non-transitory computer readable medium according to claim 8 that stores instructions for:

receiving or generating an input image;

generating a signature of the input image;

searching in the signature of the input image for at least one of (a) one or more certain first image identifier of the at least one certain first image identifier, and (b) at least one certain second image identifier of the certain second image identifiers; and

determining that the input image includes the object when the signature of the input image comprises the at least one of (a) one or more certain first image identifier of the at least one certain first image identifier, and (b) the at least one certain second image identifier.

30. The non-transitory computer readable medium according to claim 8 each one of the at least one certain first image identifier differs from each one of the certain second image identifiers,

31. The non-transitory computer readable medium according to claim 8 each one of the at least one certain first image identifier is not similar to each one of the certain second image identifiers.

15. An object detector for scale invariant object detection, that comprises:

an input that is configured to receive a first image in which an object appears in a first scale and a second image in which the object appears in a second scale that differs from the first scale;

a signature generator that is configured to generate a first image signature and a second image signature;

wherein the first image signature comprises a first group of at least one certain first image identifier that identifies at least a part of the object;

wherein the second image signature comprises a second group of certain second image identifiers that identify different parts of the object;

wherein the second group is larger than the first group; and

an object detection determination unit that is configured to link between the at least one certain first image identifier and the certain second image identifiers.

16. The object detector according to claim 15 wherein the object detection determination unit is configured to link between the first image signature, the second image signature and the object.

17. The object detector according to claim 15 wherein the object detection determination unit is configured to add the first signature and the second signature to a certain concept structure that is associated with the object.

18. The object detector according to claim 17 wherein the input is configured to receive an input image;

wherein the signal generator is configured to generate a signature of the input image;

wherein the object detection determination unit is configured to compare the signature of the input image to signatures of the certain concept structure, and to determine that the input image comprises the object when at least one of the signatures of the certain concept structure matches the signature of the input image.

19. The object detector according to claim 15, wherein the input is configured to receive an input image;

wherein the signature generator is configured to generate a signature of the input image, the signature of the input image comprises only some of the certain second image identifiers;

wherein the input image is of the second scale;

wherein the input is configured to receive an amended input image that was generated by changing a scale of the input image to the first scale;

wherein the signature generator is configured to generate a signature of the amended input image; and

wherein the object detection determination unit is configured to verify that the input image comprises the object when the signature of the amended input image comprises the at least one certain first image identifier.

20. The object detector according to claim 15, wherein the input is configured to receive an input image;

wherein the signature generator is configured to generate a signature of the input image;

wherein the object detection determination unit is configured to search in the signature of the input image for at least one of (a) the at least one certain first image identifier, and (b) the certain second image identifiers; and

determine that the input image includes the object when the signature of the input image comprises the at least one of (a) the at least one certain first image identifier, and (b) the certain second image identifiers.

21. The object detector according to claim 15 wherein the input is configured to receive an input image;

wherein the signature generator is configured to generate a signature of the input image;

wherein the object detection determination unit is configured to search in the signature of the input image for at least one of (a) one or more certain first image identifier of the at least one certain first image identifier, and (b) at least one certain second image identifier of the certain second image identifiers; and

determine that the input image includes the object when the signature of the input image comprises the at least one of (a) one or more certain first image identifier of the at least one certain first image identifier, and (b) the at least one certain second image identifier.

32. The object detector according to claim 15 wherein each one of the at least one certain first image identifier differs from each one of the certain second image identifiers.

33. The object detector according to claim 15 wherein each one of the at least one certain first image identifier is not similar to each one of the certain second image identifiers.

22. (canceled)

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