Multi-view Display Optimization via Dynamic View Adjustment
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Solution Overview
Problem
Multi-view displays face limitations in the number of distinct views they can output due to resolution and frame rate constraints, making it difficult to accommodate varying numbers of viewers, especially when people move between zones or enter/exit a room, leading to suboptimal viewing experiences.
Innovation Solution
A dynamic optimization mechanism that uses eye tracking and an anticipation algorithm to adjust viewing parameters based on viewer position and device capabilities, anticipating and adapting to state changes by degrading or enhancing views as necessary to maintain a smooth viewing experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the number of views in a multi-view display is increased, then more people can watch simultaneously, but the resolution of each view degrades
Solution Approach 1:
The system dynamically adjusts the number of views and their parameters based on real-time detection of viewer presence and position. The optimization mechanism continuously modifies viewing parameters (brightness, color values) and view configurations according to an optimization model, allowing the display to transition between different view states (personal view, non-personal view, 3D view, 2D view) to maintain quality while accommodating varying numbers of viewers
Solution Approach 2:
The patent changes the parameters of existing views rather than simply increasing the number of views. The optimization mechanism adjusts viewing parameters such as brightness and color values, and can transform view types (e.g., from personal view to non-personal view, from 3D view to 2D view) to optimize the balance between the number of views and the quality of each view based on current viewer conditions
2Quantity of substance
If the number of views in a multi-view display is increased, then more people can watch simultaneously, but the frame rate for each view reduces
Solution Approach 1:
The system dynamically adjusts the number of views and their parameters based on real-time detection of viewer presence and position. The optimization mechanism continuously modifies viewing parameters (brightness, color values) and view configurations according to an optimization model, allowing the display to transition between different view states (personal view, non-personal view, 3D view, 2D view) to maintain quality while accommodating varying numbers of viewers
Solution Approach 2:
The patent changes the parameters of existing views rather than simply increasing the number of views. The optimization mechanism adjusts viewing parameters such as brightness and color values, and can transform view types (e.g., from personal view to non-personal view, from 3D view to 2D view) to optimize the balance between the number of views and the quality of each view based on current viewer conditions
3Adaptability or versatility
If the display accommodates more viewers than its view capabilities, then more people can be served, but the viewing quality deteriorates
Solution Approach 1:
The system uses eye tracking components and optimization mechanisms to automatically detect viewer presence, position, and movement, and self-adjusts the view configuration without manual intervention. The anticipation algorithm predicts when viewers will move between zones and pre-adjusts views accordingly, enabling the display to serve varying numbers of viewers while maintaining optimal viewing quality through automated adaptation
Solution Approach 2:
The system continuously monitors viewer positions and view states through eye tracking components, and uses this feedback to dynamically adjust view configurations. The optimization mechanism receives feedback about current viewer conditions and modifies viewing parameters and view assignments accordingly, creating a closed-loop system that maintains viewing quality while adapting to changing viewer conditions
Data Source
AI summary
Described herein is a multi-view display (based on spatial and/or temporal multiplexing) having an optimization mechanism that dynamically adjust views based upon detected state changes with respect to one or more views. The optimization mechanism determines viewing parameters (e.g., brightness and/or colors) for a view based upon a current position of the view, and/or on the multi-view display's capabilities. The state change may correspond to the view (a viewer's eye) moving towards another viewing zone, in which event new viewing parameters are determined, which may be in anticipation of entering the zone. Another state change corresponds to more views being needed than the display is capable of outputting, whereby one or more existing views are degraded, e.g., from 3D to 2D and/or from a personal video to a non-personal view. Conversely, a state change corresponding to excess capacity becoming available can result in enhancing a view to 3D and/or personal.


