Dynamic Frame Rate Adjustment for Bandwidth Optimization
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Solution Overview
Problem
Conventional digital surveillance systems face bandwidth constraints, leading to reduced video quality and frame rates, which results in blurred images of moving objects, especially in environments with limited network bandwidth or unstable connections.
Innovation Solution
A dynamic adjustment method and system that cyclically samples images and adjusts frame rates based on image variation rates within specific time windows, reducing data flow by lowering frame rates when image stability is high and increasing them when significant changes occur, thereby optimizing bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the frame per second is increased to improve image quality of moving objects, then the image quality improves, but the data volume and bandwidth consumption increase
Solution Approach 1:
The patent applies dynamics by making the frame per second adjustable rather than fixed. The system dynamically changes the frame rate based on real-time image variation detection: when image variation exceeds a threshold (indicating moving objects), the frame per second is increased to capture motion details; when image variation is below the threshold (stationary scenes), the frame per second is reduced to minimize data volume. This dynamic adjustment resolves the contradiction between maintaining high image quality and reducing data consumption.
Solution Approach 2:
The patent changes the parameter of frame per second based on image variation analysis. By computing the difference between consecutive image frames and comparing it to a threshold, the system determines whether to adjust the frame rate parameter. This parameter change strategy allows the system to optimize the balance between image quality and data volume adaptively, rather than using a fixed frame rate.
2Loss of energy
If the frame per second is set to a fixed low rate to reduce bandwidth consumption, then the bandwidth usage is reduced, but the image quality of moving objects deteriorates
Solution Approach 1:
The system transitions from a static fixed frame rate to a dynamic adjustable frame rate. By continuously monitoring image variation and adjusting the frame per second accordingly, the system ensures high frame rates are used only when necessary (when moving objects are detected), thereby maintaining image quality while minimizing overall bandwidth consumption during stationary periods.
Solution Approach 2:
The frame per second parameter is changed based on image variation analysis. When the computed image variation exceeds a predefined threshold, the system increases the frame rate to capture moving objects clearly; when variation is below the threshold, the system reduces the frame rate to conserve bandwidth. This conditional parameter adjustment resolves the contradiction between bandwidth efficiency and image quality.
3Adaptability or versatility
If the resolution is reduced to adapt to limited network bandwidth, then the bandwidth constraints are satisfied, but the overall video quality deteriorates
Solution Approach 1:
The patent applies dynamics by making the frame rate adaptable to network conditions and scene content. Instead of permanently reducing resolution, the system dynamically adjusts the frame per second based on image variation, allowing full resolution to be maintained when needed (during motion) while reducing data transmission during stationary periods. This dynamic adaptation preserves video quality while satisfying bandwidth constraints.
Solution Approach 2:
The system changes the frame per second parameter based on image variation analysis rather than permanently reducing resolution. This parameter change allows the system to maintain high video quality when motion is detected while reducing overall data volume to adapt to bandwidth limitations, avoiding the quality deterioration that would result from permanent resolution reduction.
Data Source
AI summary
The present invention relates to a dynamic adjustment method for adjusting a frame per second. The method includes steps of cyclically sampling a first image and a second image captured by an image capturing device based on a sampling time interval and uploading the first image and the second image to a server; executing an image variation rate algorithm on the server to acquire an image variation rate by comparing the first image with the second image; and adjusting the frame per second for the image capturing device to a first frame per second when all of the image variation rates within a first time window are less than a first threshold.