System, device, and method for determining predicted annoyance level of multimedia content

1. A method comprising:

processing content of a plurality of frames of a content-item, and determining a Predicted Annoyance Level (PAL) score that indicates a predicted level of annoyance that said content-item is predicted to cause viewers due to motion of content in said content-item;

wherein determining the predicted level of annoyance of said content-item is based on:

(i) a calculated percentage of similar area of content between consecutive frames of the content-item; and

(ii) a number of new objects that are introduced between consecutive frames of the content-item; and

(iii) a level of object motion between consecutive frames of the content-item; and

(iv) a quantification of a level of similarity between the first frame of the content-item and the last frame of the content item.

2. The method of claim 1 ,

wherein the determining of the PAL score is based on comparison of content of pairs of frames of said content-item, wherein content of each frame is compared to content of a preceding frame, except for the first frame of the content item which is compared to the last frame of the content item.

3. The method of claim 2 ,

wherein the determining of the PAL score is based at least on a determination of an area of each frame, which is identical or is sufficiently similar beyond a pre-defined threshold level of similarity, to a corresponding area of said preceding frame.

4. The method of claim 3 ,

wherein the determining of the PAL score is further based at least on a determination of an area of each frame which comprises new content relative to said preceding frame.

5. The method of claim 1 ,

wherein the determining of the PAL score is further based at least on a determination of an area of each frame which comprises content having low motion relative to said preceding frame and based on a threshold value defining which in-frame motion is low motion.

6. The method of claim 1 ,

wherein the determining of the PAL score further comprises:

checking whether the content-item has a frame rate that is smaller than a pre-defined threshold value;

if the checking result is positive, then: modifying the PAL score to indicate a greater predicted level of annoyance.

7. The method of claim 1 ,

wherein the determining of the PAL score further comprises:

if a frame rate of said content item has a first value, then applying to said PAL score a first modification computation;

if the frame rate of said content item has a second, different value, then applying to said PAL score a second, different, modification computation.

8. The method of claim 1 ,

wherein the determining of the PAL score further comprises:

checking whether the content-item has a non-looped time duration that is greater than a pre-defined threshold value;

if the checking result is positive, then: modifying the PAL score to indicate a smaller predicted level of annoyance.

9. The method of claim 1 ,

wherein the determining of the PAL score further comprises:

if a non-looped time duration of said content item has a first value, then applying to said PAL score a first modification computation;

if a non-looped time duration of said content item has a second value, then applying to said PAL score a first modification computation.

10. The method of claim 1 , further comprising:

if the PAL score of the content-item is smaller than a pre-defined threshold value, then: generating and transmitting a notification message, to an entity that provided said content-item, indicating that the content-item is predicted to have a high level of annoyance towards viewers.

11. The method of claim 1 , further comprising:

if the PAL score of the content-item is smaller than a pre-defined threshold value, then: suspending utilization of said content-item as an advertising content-item in an online advertising platform.

12. The method of claim 1 , further comprising:

if the PAL score of the content-item is smaller than a pre-defined threshold value, then: suspending utilization of said content-item as an advertising content-item in an online advertising platform; and selecting another content-item, having a greater PAL score, for utilization in said online advertising platform.

13. The method of claim 1 , further comprising:

performing said method in a stand-alone computerized application for creation of content-items as part of a process of creating or editing a content-item;

if the PAL score of the content-item is smaller than a pre-defined threshold value, then: generating a notification message in said stand-alone computerized application for creation of content-items, indicating that the content-item is predicted to have a high level of annoyance towards viewers.

14. The method of claim 1 , further comprising:

performing said method in a cloud-based computerized application for creation of content-items as part of a process of creating or editing a content-item;

if the PAL score of the content-item is smaller than a pre-defined threshold value, then: generating a notification message in said cloud-based computerized application for creation of content-items, indicating that the content-item is predicted to have a high level of annoyance towards viewers.

15. The method of claim 1 , further comprising:

automatically processing a batch of content-items that are stored in a repository of a Content Delivery Network (CDN) or of a cloud-based hosting service; wherein said processing comprises generating a PAL score for each of said content-items;

automatically generating a report listing content-items having a PAL score that is within a pre-defined range of PAL score values.

16. A non-transitory storage medium having stored thereon instructions that, when executed by one or more processors, cause the one or more processor to perform a method comprising:

processing content of a plurality of frames of a content-item, and determining a Predicted Annoyance Level (PAL) score that indicates a predicted level of annoyance that said content-item is predicted to cause viewers due to motion of content in said content-item;

wherein determining the predicted level of annoyance of said content-item is based on:

(i) a calculated percentage of similar area of content between consecutive frames of the content-item; and

(ii) a number of new objects that are introduced between consecutive frames of the content-item; and

(iii) a level of object motion between consecutive frames of the content-item; and

(iv) a quantification of a level of similarity between the first frame of the content-item and the last frame of the content item.

17. A system comprising:

one or more processors, operably associated with one or more memory units,

wherein the one or more processors are configured:

to process content of a plurality of frames of a content-item, and

to generate a Predicted Annoyance Level (PAL) score that indicates a predicted level of annoyance that said content-item is predicted to cause viewers due to motion of content in said content-item;

wherein the predicted level of annoyance of said content-item is generated based on:

(i) a calculated percentage of similar area of content between consecutive frames of the content-item; and

(ii) a number of new objects that are introduced between consecutive frames of the content-item; and

(iii) a level of object motion between consecutive frames of the content-item; and

(iv) a quantification of a level of similarity between the first frame of the content-item and the last frame of the content item.