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US 12,120,312 B2Granted
Video encoding rate control for intra and scene change frames using machine learning
AssigneeIntel Corporation
InventorsXimin Zhang, Sang-hee Lee, Keith W. Rowe
Life of this patent
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Abstract
Techniques related to quantization parameter estimation for coding intra and scene change frames are discussed. Such techniques include generating features based on an intra or scene change frame including a proportion of smooth blocks and one or both of a measure of block variance and a prediction distortion, and applying a machine learning model to generate an estimated quantization parameter for encoding the intra or scene change frame.
Claims20
A system for video coding comprising:
- a memory to store at least a portion of an intra or scene change frame of input video;
- and
- one or more processors coupled to the memory, the one or more processors to:
- generate a plurality of features based on the intra or scene change frame, the features comprising a proportion of smooth blocks corresponding to the intra or scene change frame and at least one of a measure of block variance of blocks corresponding to the intra or scene change frame or a prediction distortion corresponding to the intra or scene change frame;
- apply a machine learning model to a first input comprising the features and a target bitrate for the intra or scene change frame to generate a first estimated quantization parameter for the intra or scene change frame;
- encode the intra or scene change frame the first estimated quantization parameter to generate a first bitstream having a number of bits;
- determine whether a difference between the target bitrate and the number of bits of the first bitstream exceeds a threshold;
- in response to determining the difference exceeds the threshold, apply the machine learning model to a second input comprising the features and the number of bits of the first bitstream to generate a second estimated quantization parameter for the intra or scene change frame;
- and
- encode the intra or scene change frame using an encode quantization parameter to generate a second bitstream, wherein the encode quantization parameter is a function of the first estimated quantization parameter and the second estimated quantization parameter.
7 more elements
A method for video encoding comprising:
- generating a plurality of features based on an intra or scene change frame of input video, the features comprising a proportion of smooth blocks corresponding to the intra or scene change frame and at least one of a measure of block variance of blocks corresponding to the intra or scene change frame or a prediction distortion corresponding to the intra or scene change frame;
- applying a machine learning model to a first input comprising the features and a target bitrate for the intra or scene change frame to generate a first estimated quantization parameter for the intra or scene change frame;
- encoding the intra or scene change frame using the first estimated quantization parameter to generate a first bitstream having a number of bits;
- determining whether a difference between the target bitrate and the number of bits of the first bitstream exceeds a threshold;
- in response to determining the difference exceeds the threshold, applying the machine learning model to a second input comprising the features and the number of bits of the first bitstream to generate a second estimated quantization parameter for the intra or scene change frame;
- and
- encoding the intra or scene change frame using an encode quantization parameter to generate a second bitstream, wherein the encode quantization parameter is a function of the first estimated quantization parameter and the second estimated quantization parameter.
4 more elements
At least one non-transitory machine readable medium comprising a plurality of instructions that, in response to being executed on a computing device, cause the computing device to perform video coding by:
- generating a plurality of features based on an intra or scene change frame of input video, the features comprising a proportion of smooth blocks corresponding to the intra or scene change frame and at least one of a measure of block variance of blocks corresponding to the intra or scene change frame or a prediction distortion corresponding to the intra or scene change frame;
- applying a machine learning model to a first input comprising the features and a target bitrate for the intra or scene change frame to generate a first estimated quantization parameter for the intra or scene change frame;
- encoding the intra or scene change frame using the first estimated quantization parameter to generate a first bitstream having a number of bits;
- determining whether a difference between the target bitrate and the number of bits of the first bitstream exceeds a threshold;
- in response to determining the difference exceeds the threshold, applying the machine learning model to a second input comprising the features and the number of bits of the first bitstream to generate a second estimated quantization parameter for the intra or scene change frame;
- and
- encoding the intra or scene change frame using an encode quantization parameter to generate a second bitstream, wherein the encode quantization parameter is a function of the first estimated quantization parameter and the second estimated quantization parameter.
4 more elements
Dependencies are inferred from the claim text.