18481590. BIT-LENGTH CONTROL FOR LINEAR REGRESSION-BASED AFFINE MERGE CANDIDATE DERIVATION simplified abstract (QUALCOMM Incorporated)
Contents
- 1 BIT-LENGTH CONTROL FOR LINEAR REGRESSION-BASED AFFINE MERGE CANDIDATE DERIVATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 BIT-LENGTH CONTROL FOR LINEAR REGRESSION-BASED AFFINE MERGE CANDIDATE DERIVATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
BIT-LENGTH CONTROL FOR LINEAR REGRESSION-BASED AFFINE MERGE CANDIDATE DERIVATION
Organization Name
Inventor(s)
Yan Zhang of San Diego CA (US)
Han Huang of San Diego CA (US)
Vadim Seregin of San Diego CA (US)
Marta Karczewicz of San Diego CA (US)
BIT-LENGTH CONTROL FOR LINEAR REGRESSION-BASED AFFINE MERGE CANDIDATE DERIVATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18481590 titled 'BIT-LENGTH CONTROL FOR LINEAR REGRESSION-BASED AFFINE MERGE CANDIDATE DERIVATION
Simplified Explanation
The example device for coding video data described in the abstract utilizes linear regression to reduce the bit length of input variables and generate an affine motion model for coding video blocks.
- The device includes memory to store video data and processors to reduce the bit length of input variables for linear regression.
- Input variables can include delta coordinates, delta motion vectors, or a value representing the number of subblocks.
- The processors perform linear regression to derive an affine motion model based on the reduced bit length input variables.
- The device codes a current block of video data based on the affine motion model.
Potential Applications
This technology can be applied in video compression algorithms, video streaming services, and video editing software.
Problems Solved
This technology helps reduce the amount of data needed to represent motion in video, leading to more efficient video coding and compression.
Benefits
The benefits of this technology include improved video quality, reduced storage requirements, and faster video processing speeds.
Potential Commercial Applications
A potential commercial application of this technology could be in the development of advanced video coding systems for streaming services.
Possible Prior Art
One possible prior art for this technology could be existing video coding algorithms that use motion estimation and compensation techniques.
Unanswered Questions
How does this technology compare to existing video coding methods?
This article does not provide a direct comparison to existing video coding methods, leaving the reader to wonder about the specific advantages and disadvantages of this approach.
What impact could this technology have on video streaming services?
The article does not discuss the potential impact of this technology on video streaming services, leaving the reader curious about how it could improve streaming quality or efficiency.
Original Abstract Submitted
An example device for coding video data includes memory configured to store the video data and one or more processors communicatively coupled to the memory. The one or more processors are configured to reduce a bit length of one or more input variables for a linear regression operation to generate one or more reduced bit length input variables, the input variables including at least one of a) one or more delta coordinates, b) one or more delta motion vectors, or c) a value representing a number of subblocks. The one or more processors are configured to perform the linear regression operation and derive an affine motion model based on the performing the linear regression on the one or more reduced bit length input variables. The one or more processors are configured to code a current block of the video data based on the affine motion model.
