INTELLIGENT VIDEO THUMBNAIL SELECTION AND GENERATION

• US 20140099034A1
• Filed: 10/10/2013
• Published: 04/10/2014
• Est. Priority Date: 10/10/2012
• Status: Active Grant

• Current Assignee: RHEI Creations Corporation
• Original Assignee: BroadbandTV, Corp. (BBTV Holdings, Inc.)
• Inventors: Rafati, Shahrzad, Fatourechi, Mehrdad, Coria, Lino
• Granted Patent: US 9,514,536 B2
• Time in Patent Office: Days
• US Class Current: 382/209
• CPC Class Codes: G06F 16/51 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/583 using metadata automatically derived from the content
• CPC Class Codes: G06F 16/739 in form of a video summary, e.g. the video summary being a video sequence, a composite still image or having synthesized frames
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06V 20/47 Detecting features for summarising video content
• CPC Class Codes: G06V 40/169 Holistic features and representations, i.e. based on the facial image taken as a whole
• CPC Class Codes: G06V 40/171 Local features and components; Facial parts eye characteristics G06V40/18; Occluding parts, e.g. glasses; Geometrical relationships

Abstract

In accordance with one embodiment, an intelligent video thumbnail selection and generation tool may select a relevant and visually stimulating image from a video file and generate a thumbnail including the image. The image may be selected by computing a relevancy metric for an image in the file based on one or more selected relevant features, and comparing that relevancy metric with the metric of at least one other image in the file. In another embodiment, a series of images in a video file may be divided into shots. One of the shots may be selected based on a shot relevancy metric and a key image from the shot may be selected as a thumbnail based on a key image relevancy metric, where the shot relevancy metric and the key image relevancy metrics may be computed based on one or more relevant content features.

Claims

1. A method comprising:

obtaining a relevancy metric for a first targeted image of a collection of images;

comparing with a computer the relevancy metric of the first targeted image with a relevancy metric of at least a second targeted image of the collection of images;

transmitting for presentation through a user interface the image having the higher relevancy metric.

2. The method of claim 1 wherein the relevancy metric for the first targeted image is based on one or more content features.

3. The method of claim 1 wherein the relevancy metric for the first targeted image indicates a relevancy of the first targeted image to the subject matter of the collection of images.

4. The method of claim 1 wherein the relevancy metric for the first targeted image comprises a visual stimulation metric.

5. The method of claim 1 and further comprising at least one of downsizing, down sampling, or filtering the collection of images.

6. The method of claim 1 wherein the relevancy metric is based on at least one of a number of faces in the first targeted image, a size of a face in the first targeted image, a number of eyes in the first targeted image, or a number of skin-colored pixels in the first targeted image.

7. The method of claim 1, wherein the relevancy metric is based on at least one of texture of the first targeted image, brightness of the first targeted image, or contrast of the first targeted image.

8. The method of claim 1 wherein the relevancy metric for the first targeted image is based on content located in an off-center position in the first targeted image.

9. The method of claim 1 and further comprising adding text, graphics, or an additional image to a selected image.

10. A method comprising:

dividing a group of images into a plurality of subgroups, each subgroup comprising a plurality of subgroup images arranged in chronological order;

selecting one of the plurality of subgroups based on a visual similarity metric; and

selecting at least one image from the selected subgroup to be a selected image based on a relevancy metric.

11. The method of claim 10, wherein the visual similarity metric is based on a number of images in the selected subgroup.

12. The method of claim 10, wherein the visual similarity metric is based on at least one of a number of faces in an image, a size of a face in an image, a number of eyes in an image, a number of “

skin-colored”

pixels in an image, texture in an image, brightness in an image, and contrast of an image.

13. The method of claim 10 wherein the relevancy metric is based on content located in an off-center position in an image.

14. The method of claim 10 and further comprising adding text, graphics, or an additional image to the selected image.

15. The method of claim 10, further comprising at least one of resizing or filtering the selected image.

16. A system comprising:

a relevancy metric for a first targeted image of a collection of images;

a computer configured to compare the relevancy metric of the first targeted image with a relevancy metric of at least a second targeted image of the collection of images;

a user interface configured to transmit for presentation the image having the higher relevancy metric.

17. The system of claim 16 wherein the relevancy metric for the first targeted image is based on one or more content features.

18. The system of claim 16 wherein the relevancy metric for the first targeted image indicates a relevancy of the first targeted image to the subject matter of the collection of images.

19. The system of claim 16 wherein the relevancy metric for the first targeted image comprises a visual stimulation metric.

20. The system of claim 16 wherein the computer is configured at least to downsize, down sample, or filter the collection of images.

21. The system of claim 16 wherein the relevancy metric is based on at least one of a number of faces in the first targeted image, a size of a face in the first targeted image, a number of eyes in the first targeted image, and a number of skin-colored pixels in the first targeted image.

22. The system of claim 16, wherein the relevancy metric is based on at least one of texture of the first targeted image, brightness of the first targeted image, or contrast of the first targeted image.

23. The system of claim 16 wherein the relevancy metric for the first targeted image is based on content located in an off-center position in the first targeted image.

24. The system of claim 16, further comprising adding text, graphics, or an additional image to a selected image.

25. A system comprising:

a visual similarity metric;

a computer configured to;

divide a group of images into a plurality of subgroups, each subgroup comprising a plurality of subgroup images arranged in chronological order;

select one of the plurality of subgroups based on a visual similarity metric; and

select at least one image from the selected subgroup to be a selected image based on a relevancy metric.

26. The system of claim 25, wherein the visual similarity metric is based on a number of images in the selected subgroup.

27. The system of claim 25, wherein the visual similarity metric is based on at least one of a number of faces in an image, a size of a face in an image, a number of eyes in an image, a number of “

skin-colored”

pixels in an image, texture in an image, brightness in an image, and contrast of an image.

28. The system of claim 25 wherein the relevancy metric is based on content located in an off-center position in an image.

29. The system of claim 25 wherein the computer is further configured to add text, graphics, or an additional image to the selected image.

30. The system of claim 25, wherein the computer is further configured to perform at least one of resizing or filtering the selected image.

31. One or more computer-readable storage media encoding computer-executable instructions for executing on a computer system a computer process, the computer process comprising:

obtaining a relevancy metric for a first targeted image of a collection of images;

comparing with a computer the relevancy metric of the first targeted image with a relevancy metric of at least a second targeted image of the collection of images;

transmitting for presentation through a user interface the image having the higher relevancy metric.

32. One or more computer-readable storage media encoding computer-executable instructions for executing on a computer system a computer process, the computer process comprising:

dividing a group of images into a plurality of subgroups, each subgroup comprising a plurality of subgroup images arranged in chronological order;

selecting one of the plurality of subgroups based on a visual similarity metric; and

selecting at least one image from the selected subgroup to be a selected image based on a relevancy metric.