Varying audio visual compression based on AI detection or classification results
AssigneeApple Inc.
InventorPeter Zatloukal
Life of this patent
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Abstract
In one embodiment, a computing device receives, from one or more cameras, a video stream comprising multiple frames, where the video stream is received at a first quality. The computing device analyzes, using a machine-learning model, images in the frames, where the machine-learning model has been trained to detect one or more objects-of-interest in the images. The computing device identifies a sequence-of-interest including consecutive frames of the video stream, where at least one object-of-interest was detected in at least one of the consecutive frames. The computing device generates a video package including the sequence-of-interest.
Claims20
A method comprising, by one or more computing devices:
- receiving a video stream comprising a plurality of frames;
- identifying a sequence-of-interest comprising a plurality of consecutive frames of the video stream, wherein at least one object-of-interest was detected, using a machine-learning model, in at least one of the plurality of consecutive frames;
- and
- selectively compressing at least a portion of the video stream to include or exclude the identified sequence-of-interest.
A device comprising:
- a memory;
- and
- at least one processor configured to:
- receive a video stream comprising a plurality of frames;
- identify a sequence-of-interest comprising a plurality of consecutive frames of the video stream, wherein at least one object-of-interest was detected, using a machine-learning model, in at least one of the plurality of consecutive frames;
- and
- selectively compress at least a portion of the video stream to include or exclude the identified sequence-of-interest.
A non-transitory machine-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
- receiving a video stream comprising a plurality of frames;
- identifying a sequence-of-interest comprising a plurality of consecutive frames of the video stream, wherein at least one object-of-interest was detected, using a machine-learning model, in at least one of the plurality of consecutive frames;
- and
- selectively compressing at least a portion of the video stream to include or exclude the identified sequence-of-interest.
Dependencies are inferred from the claim text.