US 12,003,831 B2
Automated content segmentation and identification of fungible content
Miquel Angel Farre Guiu, Bern (CH); Marc Junyent Martin, Barcelona (ES); and Pablo Pernias, Sant Joan d'Alacant (ES)
Assigned to Disney Enterprises, Inc., Burbank, CA (US)
Filed by Disney Enterprises, Inc., Burbank, CA (US)
Filed on Jul. 2, 2021, as Appl. No. 17/366,675.
Prior Publication US 2023/0007365 A1, Jan. 5, 2023
Int. Cl. H04N 21/845 (2011.01); G06N 20/00 (2019.01); H04N 21/466 (2011.01); H04N 21/8352 (2011.01)
CPC H04N 21/8456 (2013.01) [G06N 20/00 (2019.01); H04N 21/4662 (2013.01); H04N 21/8352 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
a computing platform including processing hardware and a system memory;
a software code stored in the system memory; and
a machine learning model trained to predict scene boundaries;
the processing hardware configured to execute the software code to:
receive content, the content including a plurality of acts each having a plurality of shots in sequence;
select one of the plurality of acts for segmentation;
identify, for each of the plurality of shots of the selected act, at least one respective representative unit of content, the at least one respective unit of content comprising at least one video frame, an audio sample, or a combination thereof;
generate, using the at least one respective representative unit of content, a respective embedding vector for each of the plurality of shots of the selected act to provide a plurality of embedding vectors; and
predict, using the machine learning model and the plurality of embedding vectors, respective scene boundaries of each of a plurality of scenes of the selected act, at least one of the plurality of scenes including more than one of the plurality of shots.