Salient video frame establishment

1. In a digital medium environment to extract multiple salient frames from a video based at least partially on entities present in one or more photos, a method implemented by at least one computing device, the method comprising:

obtaining, by the at least one computing device, a video including multiple frames;

obtaining, by the at least one computing device, multiple photos which are extrinsic to the video;

ascertaining, by the at least one computing device, multiple relevant entities in the video based on the multiple photos extrinsic to the video;

determining, by the at least one computing device, multiple candidate frames from the multiple frames of the video;

establishing, by the at least one computing device, multiple salient frames, in part, by:

filtering the multiple candidate frames based on the multiple relevant entities based on the multiple photos which are extrinsic to the video, and

computing multiple salient scores for the multiple candidate frames, each respective salient score corresponding to a respective candidate frame, each respective salient score is based on an image quality indicator of the each of the respective candidate frame and a relevancy score computed for at least one entity appearing in the respective candidate frame; and

controlling, by the at least one computing device, presentation of the multiple salient frames via a user interface.

2. The method as described in claim 1 , wherein the obtaining of the multiple photos comprises retrieving the multiple photos from an image library based on a time associated with the video and a temporal threshold.

3. The method as described in claim 1 , wherein the image quality indicator comprises at least one of a frame focus level or a frame brightness level.

4. The method as described in claim 1 , wherein the ascertaining comprises:

detecting a relevant entity in at least one photo of the multiple photos;

recognizing the detected relevant entity; and

assigning an entity identifier to the recognized relevant entity.

5. The method as described in claim 4 , wherein:

the ascertaining further comprises:

determining an occurrence value for the recognized relevant entity across the multiple photos; and

associating the occurrence value with the entity identifier; and

the establishing further comprises establishing the multiple salient frames based on the occurrence value associated with the entity identifier.

6. The method as described in claim 1 , wherein the multiple relevant entities comprise at least one of relevant faces or relevant objects.

7. The method as described in claim 1 , wherein:

the ascertaining comprises computing a relevancy score for each relevant entity of the multiple relevant entities based on the multiple photos; and

the establishing further comprises:

ranking the multiple candidate frames based on the multiple salient scores, and

selecting the multiple salient frames based on the ranking of the multiple candidate frames.

8. The method as described in claim 1 , wherein:

the establishing further comprises ranking the multiple salient frames; and

the controlling further comprises causing the multiple salient frames to be displayed based on the ranking of the multiple salient frames.

9. At least one computing device operative in a digital medium environment to extract frames from a video based at least partially on entities present in one or more photos, the at least one computing device comprising:

a processing system and at least one computer-readable storage medium including:

a relevant entity ascertainment module configured to ascertain multiple relevant entities based on multiple photos, wherein the multiple photos are extrinsic to the video;

a candidate frame determination module configured to determine multiple candidate frames from multiple frames of the video;

a salient frame establishment module configured to establish multiple salient frames, at least in part, by:

filtering the multiple candidate frames based on the multiple relevant entities, and

computing multiple salient scores for the multiple candidate frames, each respective salient score corresponding to a respective candidate frame, each respective salient score is based on an image quality indicator of the respective candidate frame and a relevancy score computed for at least one entity appearing in the respective candidate frame; and

a salient frame output module configured to control presentation of the multiple salient frames via a user interface.

10. The at least one computing device described in claim 9 , wherein the relevant entity ascertainment module is configured to compute the relevancy score for each respective corresponding relevant entity of the multiple relevant entities.

11. The at least one computing device as described in claim 10 , wherein the relevant entity ascertainment module is configured to compute each relevancy score based on an occurrence value that depends on a number of occurrences of the respective corresponding relevant entity across the multiple photos.

12. The at least one computing device as described in claim 9 , wherein the salient frame output module includes a collage creation module configured to create a static collage using at least a portion of the multiple salient frames.

13. The at least one computing device as described in claim 12 , wherein the collage creation module is configured to create the static collage using at least the portion of the multiple salient frames responsive to user input directed to a presentation of the multiple salient frames.

14. At least one computing device operative in a digital medium environment to extract frames from a video based at least partially on entities present in one or more photos, the at least one computing device including hardware components comprising a processing system, one or more computer-readable storage media storing computer-readable instructions that are executable by the processing system to perform operations comprising:

computing a relevancy score for each respective one of multiple relevant entities based on a presence of a corresponding relevant entity in at least one photo of multiple photos, wherein the multiple photos are extrinsic to the video;

computing a salient score for each respective one of multiple candidate frames from multiple frames of a video, each respective salient score corresponding to a respective candidate frame, each respective salient score is based on an image quality indicator of the respective candidate frame and incorporating the respective relevancy score responsive to an appearance of the corresponding relevant entity in the respective candidate frame;

establishing multiple salient frames of the multiple candidate frames using a ranking of the multiple candidate frames that is based on the respective salient scores of the multiple candidate frames; and

causing at least a portion of the multiple salient frames to be presented via a user interface.

15. The at least one computing device as described in claim 14 , wherein:

the one or more attributes of the video comprise at least one of a per-frame focus level indicator, a per-frame brightness level indicator, or a length of time a recognized entity appears in the video; and

the presence of the corresponding relevant entity comprises at least one of a number of occurrences across the multiple photos, a proportional spatial coverage over at least one photo of the multiple photos, or a positional presence in at least one photo of the multiple photos.

16. The method as described in claim 1 , wherein at least one of the multiple scenes includes consecutive frames, each of which displays an object such that the displayed object appears at an angle in one of the consecutive frames and another angle in at least another one of the consecutive frames.

17. The at least one computing device as described in claim 9 , wherein at least one of the multiple scenes includes consecutive frames, each of which displays an object such that the displayed object appears at an angle in one of the consecutive frames and another angle in at least another one of the consecutive frames.

18. The at least one computing device as described in claim 9 , wherein the relevant entity ascertaining module ascertains multiple relevant entities by:

detecting a relevant entity in at least one photo of the multiple photos;

recognizing the detected relevant entity; and

assigning an entity identifier to the recognized relevant entity.

19. The method as described in claim 18 , further comprising:

determining an occurrence value for the recognized relevant entity across the multiple photos; and

associating the occurrence value with the entity identifier.

20. The at least one computing device as described in claim 14 , wherein the multiple relevant entities comprise at least one of relevant faces or relevant objects.