Adaptive Video Decoder Using Sensor Data for Viewing Experience
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Solution Overview
Problem
Existing video decoding technologies do not optimally adapt to varying user environments and constraints, leading to sub-optimal user experience and inefficient resource usage, as they rely on manual configuration and do not account for dynamic viewing conditions.
Innovation Solution
A video decoder that estimates user viewing experience based on sensor data and analyzes constraints to select optimal decoder parameters, automatically adjusting codec capabilities to balance user experience and resource usage, including computational requirements, memory, and bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration of viewing profile is used, then user can adapt image processing profile, but system complexity increases and adaptation is limited
Solution Approach 1:
The system automatically detects viewing conditions using sensors (ambient light sensors, proximity sensors, gyroscopes) and selects appropriate decoder parameters without requiring manual user configuration. The estimator component continuously monitors sensor data and autonomously adjusts decoding parameters based on detected environmental context.
Solution Approach 2:
The system dynamically adapts decoder parameters in real-time based on changing viewing conditions. The estimator continuously processes sensor data and the selector dynamically switches between different decoder parameter sets to match current viewing context, making the system flexible and responsive to environmental changes.
2Manufacturing precision
If scalable video layers are used, then video quality can be increased or decreased, but bandwidth consumption increases
Solution Approach 1:
The system changes decoder parameters (such as resolution, frame rate, bitrate) based on detected viewing conditions. When viewing distance is large or ambient light is poor, the system selects parameter sets that prioritize quality. When bandwidth is constrained or viewing conditions are optimal, it reduces parameters to save bandwidth.
Solution Approach 2:
The system applies partial adaptation by selecting only the necessary decoder parameters to achieve acceptable quality for current viewing conditions, rather than always using maximum quality settings. This provides sufficient video quality while consuming less bandwidth than full scalable video layers.
3Quantity of substance
If decoder parameters are optimized for compression, then bandwidth usage decreases, but user viewing experience may degrade
Solution Approach 1:
The system dynamically adjusts decoder parameters based on viewing conditions to maintain optimal balance between compression and quality. In good viewing conditions (close distance, proper lighting), it uses higher compression. In poor conditions, it reduces compression to maintain quality, ensuring reliable viewing experience across different contexts.
Solution Approach 2:
The estimator provides feedback about viewing conditions to the selector, which adjusts decoder parameters accordingly. This closed-loop system continuously monitors sensor data and adapts parameters to maintain viewing experience while optimizing bandwidth usage based on actual environmental context.
4Adaptability or versatility
If automatic parameter selection based on sensors is implemented, then adaptability to viewing conditions improves, but device complexity increases
Solution Approach 1:
The system uses existing multi-functional sensor components (ambient light sensors, proximity sensors, gyroscopes) that serve multiple purposes in the device. By leveraging these existing sensors for viewing condition detection, the system achieves automatic adaptation without adding dedicated hardware complexity.
Solution Approach 2:
The estimator acts as an intermediary component that processes sensor data and translates it into meaningful viewing context information for the parameter selector. This mediator layer simplifies the complexity by providing a standardized interface between diverse sensor inputs and the parameter selection logic.
Data Source
AI summary
Video decoder adapted for decoding video based on decoder parameters selected from variable decoder parameters, the decoder comprising an estimator adapted to estimate user viewing experience based on sensor data and comprising a constraint analyzer adapted to analyze constraints when using the decoder parameters, the video decoder further comprising a selector adapted to select said decoder parameters from the variable decoder parameters, wherein the selector is coupled to the estimator and the constraint analyzer.