Video Frame Warping With ROI Encoding for Face Distortion
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Solution Overview
Problem
Existing video coding methods using warp operations for temporal prediction can cause unwanted distortions, particularly in regions of human faces, leading to an 'uncanny valley' effect, which are difficult to detect algorithmically and affect the quality of reconstructed video frames.
Innovation Solution
Identify regions of interest, such as human eyes and mouths, in video frames and transmit encoded image data for these regions separately, using an external image encoder, while applying a warp operation to the entire frame for approximation, allowing for a more pleasing image without requiring complex distortion detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a warp operation is used to reconstruct a video frame, then data transmission efficiency is improved and bitrate is reduced, but image quality deteriorates due to unwanted distortions in regions of interest
Solution Approach 1:
The video frame is divided into regions of interest (such as human face, eyes, mouth) and non-interest regions. Different encoding strategies are applied to each segment: warp operations are used for non-interest regions to reduce data transmission, while full-resolution encoding is applied to regions of interest to maintain image quality and avoid distortions.
Solution Approach 2:
Different quality levels are applied to different parts of the video frame based on their importance. Regions of interest receive high-quality full-resolution encoding to prevent distortions, while less important regions use compact warp operations. This local differentiation resolves the contradiction by maintaining quality where needed while improving overall transmission efficiency.
2Loss of information
If a warp operation is used for temporal prediction, then compact representation of video data is achieved, but unwanted distortions occur in sensitive regions such as eyes and mouth
Solution Approach 1:
Regions of interest that are susceptible to harmful distortion effects are extracted and separated from the rest of the video frame. These extracted regions are then encoded separately using full-resolution methods, removing them from the warp operation process that causes distortions, while the remaining video data continues to use compact warp encoding.
3Manufacturing precision
If encoded image data for the entire video frame is transmitted, then image quality is maintained, but data transmission requirements increase
Solution Approach 1:
The video frame is segmented into regions of interest and non-interest regions. Only the essential regions (faces, eyes, mouth) are encoded at full resolution and transmitted, while other regions use compact warp representations. This segmentation maintains image quality for important areas while significantly reducing overall data transmission volume.
Solution Approach 2:
Instead of encoding the entire video frame at full resolution, only the necessary portions (regions of interest) are encoded and transmitted at high quality. This partial action approach maintains sufficient image quality for the most important areas while avoiding the excessive data transmission that would result from encoding the complete frame.
Data Source
AI summary
A computer-implemented method of transmitting video data. A sequence of video frames is received. A warp operation for a first frame and a reference frame of the sequence of video frames is determined, wherein the warp operation defines a transformation of the reference frame to give an approximation of the first frame. One or more regions of interest of the first frame are identified. Encoded image data from the image data of the one of more regions of interest of the first frame is generated using an image encoder. The warp operation and the encoded image data are transmitted.