Audiovisual Enhancement Using Receiver Feedback for Adaptive Quality
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Solution Overview
Problem
Existing audiovisual communication systems face challenges in optimizing audiovisual enhancement functions due to static application methods that do not consider dynamic changes in receiver environments and hardware, leading to suboptimal resource usage and perceptual quality.
Innovation Solution
Implementing systems and methods that apply audiovisual enhancement functions selectively based on receiver feedback signals, such as gaze detection and ambient noise recognition, to dynamically adjust audio and video fidelity in real-time, optimizing resource usage and perceptual quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed optimization techniques are used for audiovisual communication, then device complexity is reduced, but perceptual quality and adaptability deteriorate
Solution Approach 1:
The system implements feedback by transmitting receiver feedback signals from the receiver computing system back to the sender computing system. These feedback signals contain information about receiver conditions (such as gaze detection, ambient noise levels, and other environmental factors), enabling the sender to dynamically adjust audiovisual enhancement functions based on actual receiver state, thereby achieving adaptability without requiring the receiver to directly control the sender's processing
Solution Approach 2:
The system transitions from fixed optimization techniques to dynamic adaptation by continuously adjusting audiovisual enhancement functions based on real-time receiver feedback. The sender computing system modifies compression, filtering, and other enhancement parameters dynamically according to the receiver's current conditions, allowing the system to adapt to changing environmental and receiver-specific factors while maintaining manageable complexity through automated feedback-driven control
2Reliability
If high quality audiovisual enhancement is applied continuously, then perceptual quality is improved, but bandwidth and power consumption increase
Solution Approach 1:
The system applies partial enhancement by selectively adjusting the degree of audiovisual enhancement based on receiver feedback conditions. Instead of continuously applying maximum enhancement, the sender computing system applies only the necessary level of enhancement required for the current receiver state. For example, when the receiver is in a low-noise environment with good viewing conditions, enhancement can be reduced, conserving bandwidth and power while maintaining adequate quality
Solution Approach 2:
The system changes processing parameters dynamically based on receiver feedback. The sender computing system adjusts parameters such as compression ratio, filtering strength, and resolution based on the receiver's environmental conditions and state. This allows the system to maintain high communication quality when needed while reducing bandwidth and power consumption when conditions permit, achieving energy efficiency without sacrificing reliability
3Adaptability or versatility
If receiver feedback signals are processed in real-time, then adaptability is improved, but processing time and complexity increase
Solution Approach 1:
The system performs preliminary action by pre-processing and analyzing receiver feedback signals as they are received, preparing enhancement parameter adjustments in advance before they are needed for the next audiovisual frame. The sender computing system anticipates the need for parameter changes by continuously monitoring feedback trends, allowing it to prepare and apply enhancements with minimal delay, thereby achieving real-time adaptation without excessive processing time
Solution Approach 2:
The feedback mechanism is designed to process receiver feedback signals efficiently by establishing a continuous feedback loop where the sender computing system receives, analyzes, and responds to feedback signals with minimal latency. The system processes feedback signals in real-time by implementing efficient analysis algorithms that can quickly determine appropriate enhancement parameter adjustments, ensuring that adaptability is achieved without significant processing time delays
Data Source
AI summary
A computer-implemented method for selectively applying audiovisual enhancement functions to an audiovisual communications stream includes transmitting, by a sender computing system, an audiovisual communication stream to a receiver computing system, obtaining, by the sender computing system, one or more receiver perception feedback signals associated with the audiovisual communication stream, the one or more receiver perception feedback signals obtained as output from one or more receiver perception feedback models at the receiver computing system and descriptive of perception of the audiovisual communication stream by a user operating the receiver computing system, and applying, by the sender computing system, one or more audiovisual enhancement functions to the audiovisual communication stream based at least in part on the one or more receiver perception feedback signals.