Camera and Object Motion Compensation in Efficient Video Coding
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Solution Overview
Problem
The increasing demand for high-quality video data places a significant burden on communication networks and devices due to the large amount of data required, necessitating more efficient video coding techniques.
Innovation Solution
Utilizing machine learning architectures, particularly neural networks, for camera and object motion compensation in video coding, including generating camera motion compensated frames, optical flow information, and motion compensated frames to reconstruct input frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional video coding techniques are used, then video quality can be maintained, but the amount of data required for transmission and processing increases significantly
Solution Approach 1:
The patent segments motion compensation into two distinct components: camera motion compensation (handling background/scene movement) and object motion compensation (handling foreground object movement). This segmentation allows each component to be optimized independently, reducing the overall data required while maintaining video quality through targeted motion representation
Solution Approach 2:
The patent introduces depth information as an additional dimension to traditional 2D video coding. By incorporating depth maps and performing 3D warping operations, the system can more accurately represent scene geometry and motion, reducing residual data while maintaining or improving reconstruction quality
2Measurement precision
If high resolution and high frame rate video is provided, then video quality improves, but the burden on communication networks and processing devices increases
Solution Approach 1:
The patent extracts and separately encodes camera motion parameters and object motion parameters from the video data. By isolating the dominant camera motion component and representing it efficiently through depth-warped reference frames, the system reduces the bit rate required for transmitting high-quality video content
Solution Approach 2:
The patent performs preliminary camera motion compensation using depth information and camera pose data before object motion compensation. This preliminary action removes the bulk of motion from the scene, allowing subsequent object motion to be encoded with fewer bits, thus reducing overall network burden while maintaining quality
Data Source
AI summary
Systems and techniques are provided for coding (e.g., encoding and/or decoding) video data using camera motion information. For example, a decoding device can obtain a frame of encoded video data associated with an input frame, the frame of encoded video data including camera information associated with generating the video data and a residual. A camera motion compensated frame can be generated based on a reference frame and the camera information. Optical flow information associated with object motion determined based on at least the input frame and the reference frame can be generated. A motion compensated frame can be generated by warping the camera motion compensated frame based on the optical flow information. A reconstructed input frame can be generated based on the motion compensated frame and the residual.