Google llc (20240098298). SEGMENTATION-BASED PARAMETERIZED MOTION MODELS simplified abstract
Contents
- 1 SEGMENTATION-BASED PARAMETERIZED MOTION MODELS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SEGMENTATION-BASED PARAMETERIZED MOTION MODELS - 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 Answer
- 1.11 Answer
- 1.12 Original Abstract Submitted
SEGMENTATION-BASED PARAMETERIZED MOTION MODELS
Organization Name
Inventor(s)
Debargha Mukherjee of Cupertino CA (US)
Yuxin Liu of Palo Alto CA (US)
Sarah Parker of San Francisco CA (US)
SEGMENTATION-BASED PARAMETERIZED MOTION MODELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240098298 titled 'SEGMENTATION-BASED PARAMETERIZED MOTION MODELS
Simplified Explanation
The patent application describes a method for decoding multiple global motion models associated with segments of a current frame from a compressed bitstream, and using these models to decode blocks of the current frame.
- Segmentation of the current frame is used to create multiple global motion models, each representing the underlying motion of blocks within a segment.
- For each inter-predicted block of a segment, an indication is decoded from the compressed bitstream to determine whether to decode the block based on a global motion model associated with the segment or based on a different motion vector.
- The inter-predicted block is then decoded based on the indication received.
Potential Applications
This technology could be applied in video compression algorithms, video streaming services, virtual reality applications, and video editing software.
Problems Solved
This technology helps improve the efficiency and accuracy of decoding video frames by utilizing multiple global motion models for different segments, leading to better motion estimation and compression.
Benefits
The use of multiple global motion models can result in higher compression ratios, reduced bandwidth requirements, improved video quality, and more accurate motion prediction in video processing applications.
Potential Commercial Applications
- "Enhancing Video Compression Efficiency with Multiple Global Motion Models"
Possible Prior Art
One possible prior art in this field is the use of motion estimation techniques in video compression algorithms to improve compression efficiency and video quality.
What are the potential limitations of this technology in real-world applications?
Answer
One potential limitation of this technology could be the computational complexity involved in decoding multiple global motion models for each segment of a video frame, which may require significant processing power.
How does this technology compare to existing methods of video frame decoding?
Answer
This technology improves upon existing methods by utilizing multiple global motion models for different segments of a video frame, leading to more accurate motion estimation and better compression efficiency.
Original Abstract Submitted
multiple global motion models associated with respective segments of a current frame are decoded from a compressed bitstream. each global motion model is based on a segmentation of the current frame and represents a respective underlying motion of blocks within a respective segment. blocks of the current frame are decoded by: for each inter-predicted block of a segment, decoding, form the compressed bitstream, an indication of whether to decode the each inter-predicted block based on a global motion model of the multiple global motion models and associated with the segment, or whether to decode the each inter-predicted block based on a motion vector that is different from the global motion model; and decoding the each inter-predicted block based on the indication.
