3D Video Compression Using Color Motion Vectors for Depth Estimation
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Solution Overview
Problem
Current 3D video compression methods require significant computational resources and data transmission bandwidth due to the complexity of compressing multi-view videos, particularly in depth video estimation, which hinders efficient transmission.
Innovation Solution
A 3D video compressing apparatus and method that utilizes a motion estimating unit to generate a color video motion vector, a depth estimating unit to generate a depth video, and an encoding unit to compress the multi-view video, depth video, and color video motion vector, while also employing a video copying unit to reuse depth video from previous frames where motion is absent, thereby reducing the need for separate depth video motion vectors and calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth video is estimated from multi-view video using motion estimation, then depth video quality is improved, but calculation amount and processing time increase significantly
Solution Approach 1:
The video sequence is divided into P-frames and B-frames. Depth video estimation is performed only on P-frames, while B-frames reuse depth information from adjacent P-frames through interpolation. This segmentation reduces the overall calculation amount while maintaining depth video quality across all frames.
Solution Approach 2:
Depth video is estimated in advance for P-frames during the compression process. These pre-estimated depth videos are then stored and reused for B-frames through temporal interpolation, avoiding redundant calculations and reducing processing time.
2Loss of information
If all multi-view videos are compressed and transmitted, then viewpoint information completeness is improved, but transmission bandwidth increases
Solution Approach 1:
Instead of transmitting all multi-view videos, the system transmits a representative view along with depth video and motion vectors. Other viewpoints are synthesized by copying and warping the transmitted view using the depth information and motion compensation, significantly reducing transmission bandwidth while maintaining viewpoint information completeness.
Solution Approach 2:
The transmitted depth video and motion vectors serve multiple purposes: they enable reconstruction of the transmitted view, facilitate synthesis of additional viewpoints, and support both compression and rendering functions. This multi-functionality reduces the need to transmit separate data for each viewpoint.
3Measurement precision
If separate depth video motion vectors are calculated, then depth video accuracy is improved, but computational load increases
Solution Approach 1:
The patent merges the motion estimation process for color video and depth video. The same motion vectors derived from color video are directly applied to depth video, eliminating the need for separate depth video motion estimation. This combining approach maintains depth video accuracy while significantly reducing computational load.
Solution Approach 2:
The motion vectors calculated for color video serve dual purposes: they drive both color video prediction and depth video prediction. This universal use of motion vectors reduces redundant calculations while maintaining the accuracy needed for both video streams.
Data Source
AI summary
A three-dimensional (3D) compressing method and apparatus is disclosed. The 3D video compressing apparatus determines whether a motion of consecutive frames exists when a depth of a multi-view video is estimated, performs a depth estimation when the motion exists, and compresses the 3D video by using a color video motion vector as a depth video motion vector.