Spherical Motion Estimation for 360-Degree Video Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video coding systems for 360° video struggle to effectively detect redundancies in two-dimensional representations of three-dimensional image content, leading to inefficient bandwidth usage due to distortions caused by the conversion of three-dimensional space into two-dimensional data.
Innovation Solution
The implementation of a video coding system that uses spherical-domain projections to predictively code 360° video data by transforming input and reference pictures into spherical representations, allowing for the detection of redundancies and efficient coding through motion vector estimation and differential coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If video coding systems use traditional two-dimensional representation for 360° video, then the coding process is simple, but bandwidth efficiency deteriorates due to undetected redundancies caused by distortions
Solution Approach 1:
The patent transforms the video coding approach from traditional two-dimensional representation to spherical-domain representation. By mapping 360° video content onto a spherical coordinate system, the coding system can properly account for the three-dimensional nature of the content, enabling accurate redundancy detection and significantly improving bandwidth efficiency while maintaining manageable complexity through systematic transformation processes
2Loss of information
If video coding systems transform to spherical-domain projections, then redundancy detection improves, but processing complexity increases
Solution Approach 1:
The patent applies spherical projection transformation as a preliminary step before motion estimation and redundancy detection. By pre-transforming the 360° video content into spherical coordinates, the system establishes a proper geometric framework that enables accurate redundancy detection without requiring complex adaptive processing during the main coding stages, thus managing overall processing complexity
3Measurement precision
If traditional motion estimation is used on distorted two-dimensional data, then processing is fast, but coding accuracy deteriorates
Solution Approach 1:
The patent changes the coordinate system parameters from Cartesian (x,y) to spherical coordinates (θ,φ) for motion estimation. This parameter transformation allows motion vectors to be calculated in a coordinate system that naturally represents the geometry of 360° video content, significantly improving motion estimation accuracy. The systematic nature of the spherical transformation maintains processing efficiency comparable to traditional methods
Data Source
AI summary
Techniques are disclosed for coding video data predictively based on predictions made from spherical-domain projections of input pictures to be coded and reference pictures that are prediction candidates. Spherical projection of an input picture and the candidate reference pictures may be generated. Thereafter, a search may be conducted for a match between the spherical-domain representation of a pixel block to be coded and a spherical-domain representation of the reference picture. On a match, an offset may be determined between the spherical-domain representation of the pixel block to a matching portion of the of the reference picture in the spherical-domain representation. The spherical-domain offset may be transformed to a motion vector in a source-domain representation of the input picture, and the pixel block may be coded predictively with reference to a source-domain representation of the matching portion of the reference picture.