Video Transmission Adaptive Resolution and Body Part Tracking
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Solution Overview
Problem
Conventional communication systems face challenges in dynamically adjusting video resolution and tracking user body parts during video calls based on channel quality and device resources, leading to suboptimal video transmission and resource utilization.
Innovation Solution
A user device equipped with an encoder, network interface, resource manager, and video controller that adjusts video resolution and selects user body parts to track based on channel quality information and resource availability, using depth detection and skeletal point processing to control the video transmission and image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If video resolution is increased to improve video quality, then video transmission quality is improved, but network bandwidth consumption increases
Solution Approach 1:
The system dynamically adjusts video resolution based on real-time channel quality conditions. The resource manager continuously monitors network conditions and modifies the video resolution parameter accordingly, transitioning between different resolution levels (e.g., 720p, 1080p, 4K) to optimize the balance between video quality and bandwidth consumption.
Solution Approach 2:
The patent changes the video resolution parameter adaptively based on channel quality information. When channel quality is good, higher resolution parameters are used; when channel quality degrades, the system switches to lower resolution parameters to maintain acceptable video transmission while reducing bandwidth consumption.
2Measurement precision
If more user body parts are tracked at higher video resolution, then tracking precision is improved, but processing complexity increases
Solution Approach 1:
The system applies different tracking granularities to different video resolution levels. At higher resolutions, more body parts are tracked with higher precision; at lower resolutions, fewer body parts are tracked. This local adaptation of tracking quality matches the available processing resources and maintains acceptable tracking performance across varying conditions.
Solution Approach 2:
The video controller selectively tracks only the necessary number of body parts based on video resolution. When resolution is high, more body parts are tracked; when resolution is low, fewer body parts are tracked. This partial action approach prevents excessive processing while maintaining sufficient tracking precision for the given video quality level.
3Productivity
If video resolution is dynamically adjusted based on channel quality, then resource utilization is optimized, but system complexity increases
Solution Approach 1:
The patent combines multiple functions into integrated components. The resource manager handles both channel quality monitoring and video resolution determination; the video controller integrates body part selection, video cropping, and zoom control. This merging reduces overall system complexity while achieving dynamic resource optimization.
Solution Approach 2:
The system performs self-adjustment of video resolution and tracking parameters based on automatic channel quality assessment. The resource manager autonomously determines appropriate resolution levels, and the video controller automatically selects and tracks relevant body parts without requiring manual intervention, thereby optimizing resource utilization while managing complexity through automation.
Data Source
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AI summary
Disclosed is a method of transmitting video via a network and a user device and computer program product configured to implement the method. The method comprises transmitting video of one or more users, received from an image capture device, to at least another user device via the network; receiving information about a communication channel between the user device and the other user device and/or about one or more resources of the user device and/or the other user device; selecting characteristics from a plurality of visual user characteristics based on the received information; and controlling the video based on detection of the selected characteristics to track the selected characteristics.