Motion-Based Frame Rate Adjustment for Conference Video
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Solution Overview
Problem
Conventional conferencing software struggles with inconsistent video stream quality due to fixed frame rates, leading to choppy movements of active participants and resource constraints, as all participants are rendered at the same frame rate regardless of their motion levels.
Innovation Solution
Implementing motion-based frame rate adjustment, where frame rates for video streams are dynamically adjusted based on the motion of individual participants within a conference room or network-connected participants, allowing higher frame rates for active or frequently moving participants while reducing for less active ones, thereby optimizing compute and network resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a fixed frame rate is used for all participants, then resource consumption is controlled, but video quality for active participants deteriorates
Solution Approach 1:
The system dynamically adjusts the frame rate for each participant based on their motion activity level. Instead of using a fixed frame rate for all participants, the frame rate is adapted in real-time according to whether a participant is active (moving) or inactive (stationary), thereby optimizing both resource consumption and video quality
Solution Approach 2:
Different frame rates are applied to different participants based on their individual motion characteristics. Active participants receive higher frame rates to maintain video quality, while inactive participants receive lower frame rates to conserve resources, creating a localized quality adjustment for each participant's video stream
2Reliability
If a high frame rate is used for all participants, then video quality is improved, but resource consumption increases
Solution Approach 1:
Instead of applying high frame rates to all participants (excessive action), the system applies high frame rates only to participants who actually need them (partial action). By identifying inactive participants and reducing their frame rates, the system avoids the excessive resource consumption that would result from uniformly high frame rates across all participants
3Reliability
If motion-based frame rate adjustment is implemented, then video quality for active participants is improved, but system complexity increases
Solution Approach 1:
The system segments participants into different categories (active and inactive) based on their motion characteristics. This segmentation allows the system to apply different frame rate strategies to different groups, simplifying the control logic compared to individually optimizing each participant while still achieving differentiated quality levels
Data Source
AI summary
During a conference, a first video stream is obtained from a first participant device connected to a local area network and a second video stream is obtained from a second participant device connected to the local area network. A first frame rate is determined for the first participant device to use based on information particular to the first video stream and based on a network constraint associated with the local area network. A second frame rate is determined for the second participant device to use based on information particular to the second video stream and based on the network constraint associated with the local area network. The first participant device and the second participant device are then instructed, during the conference, to respectively capture the first video stream at the first frame rate and the second video stream at the second frame rate.