Cross-View Motion Vector Prediction for Multiview Video Coding
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Solution Overview
Problem
Existing video coding methods for multiview video (MVV) do not effectively utilize the statistical redundancy between different views, leading to inefficient bitrate usage.
Innovation Solution
Implement disparity-compensated prediction by including pictures of other views in the reference picture list to derive motion vector predictors, reducing statistical redundancy and improving coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simulcast coding is used to encode each view independently, then device complexity is reduced and ease of operation is improved, but coding efficiency deteriorates and bitrate increases
Solution Approach 1:
The patent merges the encoding processes of multiple views by allowing motion vectors from one view to predict motion vectors in another view. This combining of prediction resources across views improves coding efficiency while maintaining operational simplicity, directly resolving the contradiction between ease of operation and coding efficiency.
2Device complexity
If simulcast coding is used to encode each view independently, then device complexity is reduced, but bitrate increases
Solution Approach 1:
The patent uses motion vectors from one view as a copy or template for predicting motion vectors in another view. This copying approach allows the system to maintain low device complexity while significantly reducing bitrate by avoiding redundant motion vector encoding across views.
3Productivity
If disparity-compensated prediction is implemented to reduce statistical redundancy, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-calculating and storing motion vectors from reference views before encoding the current view. This preliminary computation enables the disparity-compensated prediction to proceed efficiently with minimal additional complexity during the main encoding process, resolving the contradiction between coding efficiency improvement and device complexity increase.
Data Source
AI summary
The various implementations described herein include methods and systems for coding video. In one aspect, a method includes receiving a multi-view video bitstream that includes a first block in a first frame corresponding to a first view and a second block in a second frame corresponding to a second view. The method identifies a first set of reference frames in the first view for the first block. The method obtains motion vectors corresponding to a second set of reference frames in the second view for the second block. In accordance with a determination that the first set of reference frames share a display time with the second set of reference frames, the method derives a motion vector predictor (MVP) for the first block corresponding to the first view using the set of motion vectors corresponding to the second view, and decodes the first block using the derived MVP.


