Adaptive Video Compression via Motion Hash Analysis
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Solution Overview
Problem
Conventional video compression methods fail to adaptively compress different frames of a video, leading to over-compression or under-compression, which results in noticeable video quality degradation, especially when frames with varying numbers of stationary and moving objects are compressed using a fixed compression rate.
Innovation Solution
A system and method that dynamically adjust the compression rate for each frame by comparing hash images to determine the number of stationary and moving objects, applying a higher compression rate for frames with more moving objects and a lower rate for frames with more stationary objects, thereby avoiding over-compression or under-compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed compression rate is applied to all frames, then the compression process is simple and fast, but frames with stationary objects are over-compressed causing noticeable quality degradation
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed compression rate to a dynamic, frame-adaptive compression rate. The system analyzes each frame's content characteristics (stationary vs. moving objects) and adjusts the compression rate accordingly, making the compression process adaptive rather than static. This resolves the contradiction by allowing high compression for moving objects while maintaining low compression for stationary objects, thus preserving quality where needed while maintaining overall efficiency.
Solution Approach 2:
The patent implements local quality by applying different compression rates to different regions or types of content within the video stream. Specifically, stationary objects receive lower compression rates to preserve detail, while moving objects receive higher compression rates. This localized differentiation resolves the contradiction by optimizing quality for critical regions while maintaining productivity for less critical regions.
2Manufacturing precision
If a fixed compression rate is applied to all frames, then the encoding process is straightforward, but frames with moving objects are under-compressed resulting in wasted bandwidth
Solution Approach 1:
The system dynamically adjusts compression rates based on frame content analysis. When moving objects are detected, the system increases the compression rate for those frames, thereby improving bandwidth efficiency without sacrificing perceived quality. This dynamic adjustment resolves the contradiction by optimizing the trade-off between quality and bandwidth usage based on actual content characteristics.
Solution Approach 2:
The patent changes the compression rate parameter adaptively based on frame content. By analyzing characteristics such as motion magnitude and object type, the system modifies the compression rate parameter in real-time, applying higher rates to frames with moving objects and lower rates to frames with stationary objects. This parameter adaptation resolves the contradiction by optimizing both quality and bandwidth efficiency.
3Manufacturing precision
If different compression rates are applied to different video types, then video quality is optimized for each type, but the compression system becomes more complex
Solution Approach 1:
The patent segments the video stream into individual frames and further segments each frame into regions with stationary objects and regions with moving objects. This segmentation allows the system to apply different compression rates to different segments based on their characteristics, optimizing quality while managing complexity through automated analysis rather than manual classification.
Solution Approach 2:
The compression system performs self-service by automatically analyzing each frame's content characteristics and determining the appropriate compression rate without external intervention. The system autonomously identifies stationary vs. moving objects and adjusts compression parameters accordingly, reducing the need for complex external control mechanisms while maintaining optimized quality.
Data Source
AI summary
Disclosed by way of example embodiments are a system and a computer implemented method for adaptively encoding a video by changing compression rates for different frames of the video. In one aspect, two frames of a video are compared to determine a compression rate for compressing one of the two frames. Hash images may be generated for corresponding frames for the comparison. By comparing two hash images, a number of stationary objects and a number of moving objects in the two frames may be determined. Moreover, a compression rate may be determined according to the number of stationary objects and the number of moving objects.