Depth-Assisted Motion Compensation for Video Encoding
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Solution Overview
Problem
Existing video encoding techniques consume significant computational resources for motion estimation, leading to high hardware costs and reduced video quality due to inefficient data processing, especially in applications like videoconferencing and surveillance.
Innovation Solution
The use of both pixel-based cameras and depth devices to segment objects, track their motion, and derive motion vectors based on constructed motion models, reducing the need for extensive motion estimation and improving compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If motion estimation is performed using traditional pixel-based methods, then video encoding can be achieved, but computational resource consumption is high and hardware costs increase
Solution Approach 1:
The patent segments the video content into foreground objects and background regions using depth information. By dividing the encoding task into separate regions with different encoding strategies, the system reduces computational resources needed for motion estimation in static background areas while maintaining encoding reliability for the entire frame.
Solution Approach 2:
The patent introduces depth maps as an intermediary data structure between the raw video frames and the motion estimation process. These depth maps provide additional spatial information that facilitates more efficient motion vector derivation, reducing the computational burden of traditional pixel-based motion estimation while preserving encoding accuracy.
2Productivity
If traditional motion estimation is used for video compression, then video can be encoded, but video quality decreases due to inefficient data processing
Solution Approach 1:
The patent performs preliminary segmentation of foreground and background regions using depth information before the main motion estimation process. This preliminary action allows the system to apply optimized encoding strategies to different regions, improving overall encoding efficiency while maintaining high video quality through more accurate motion compensation.
Solution Approach 2:
The patent applies different encoding qualities and strategies to different spatial regions based on their importance. Foreground regions containing objects receive higher quality encoding with more accurate motion compensation, while background regions use more efficient but lower complexity methods, thereby optimizing overall video quality relative to computational resources.
3Productivity
If depth information is integrated into motion compensation, then compression efficiency increases, but device complexity increases
Solution Approach 1:
The patent designs the encoding system to handle both depth map processing and color frame encoding within a unified framework. The same motion estimation and compensation modules process both traditional pixel data and depth-derived information, allowing the system to achieve improved compression efficiency without requiring entirely separate hardware subsystems for each function.
Data Source
AI summary
An apparatus comprising a plurality of ports, and a processor coupled to the ports and configured to receive a plurality of video frames from any of the ports, wherein the video frames comprise an object and a background, and wherein the video frames comprise a plurality of color pixels for the object and the background, receive a plurality of depth frames from any of the ports, wherein the depth frames comprise the object and the background, and wherein the depth frames comprise an indication of an object depth relative to a background depth, and encode the video frames using the indication of the object depth relative to the background depth.