US 11,776,273 B1
Ensemble of machine learning models for automatic scene change detection
Shixing Chen, Seattle, WA (US); Muhammad Raffay Hamid, Seattle, WA (US); Vimal Bhat, Redmond, WA (US); and Shiva Krishnamurthy, Sammamish, WA (US)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Nov. 30, 2020, as Appl. No. 17/107,514.
This patent is subject to a terminal disclaimer.
Int. Cl. G06V 20/40 (2022.01); G06N 5/04 (2023.01); G06N 20/20 (2019.01); G10L 25/78 (2013.01); G06F 18/213 (2023.01)
CPC G06V 20/49 (2022.01) [G06F 18/213 (2023.01); G06N 5/04 (2013.01); G06N 20/20 (2019.01); G10L 25/78 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving a request to train an ensemble of machine learning models, on a training dataset of videos having labels that indicate scene changes, to detect a scene change in a video;
partitioning each video file of the training dataset of videos into a plurality of shots;
training the ensemble of machine learning models into a trained ensemble of machine learning models based at least in part on the plurality of shots of the training dataset of videos and the labels that indicate scene changes;
receiving an inference request for an input video;
partitioning the input video into a plurality of shots;
generating, by the trained ensemble of machine learning models, an inference of one or more scene changes in the input video based at least in part on the plurality of shots of the input video; and
transmitting the inference to a client application or to a storage location.