View source for Google llc (20240098298). SEGMENTATION-BASED PARAMETERIZED MOTION MODELS simplified abstract

=SEGMENTATION-BASED PARAMETERIZED MOTION MODELS=


==Organization Name==

[[:Category:google llc|google llc]]


[[Category:google llc]]

==Inventor(s)==

[[:Category:Debargha Mukherjee of Cupertino CA (US)|Debargha Mukherjee of Cupertino CA (US)]][[Category:Debargha Mukherjee of Cupertino CA (US)]]

[[:Category:Yuxin Liu of Palo Alto CA (US)|Yuxin Liu of Palo Alto CA (US)]][[Category:Yuxin Liu of Palo Alto CA (US)]]

[[:Category:Sarah Parker of San Francisco CA (US)|Sarah Parker of San Francisco CA (US)]][[Category: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.



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