Selective Focus Imaging for Dynamic Region Processing
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Solution Overview
Problem
Conventional natural user interface (NUI) systems process all information from a scene equally, regardless of whether it is static or dynamic, leading to inefficiencies in focusing on areas of interest within the field of view.
Innovation Solution
The system selectively focuses on areas of interest by providing more image detail through methods such as mechanical or digital zoom, increasing pixel density, and adjusting light incidence, while storing and reusing data from outside areas to maintain frame rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional NUI systems process all information from a scene equally, then complete scene coverage is achieved, but processing efficiency and focus on dynamic areas deteriorate
Solution Approach 1:
The patent segments the scene into multiple regions of interest (ROIs) based on detected objects or activities. Each ROI is processed independently with higher detail, while other areas are processed at lower resolution or skipped entirely. This segmentation allows the system to focus computational resources on dynamic areas while maintaining complete scene coverage, resolving the contradiction between processing efficiency and information completeness.
Solution Approach 2:
The patent applies local quality enhancement by increasing image detail and processing resolution specifically within identified regions of interest. The system dynamically adjusts the quality level for different spatial locations based on their importance, applying high-quality processing to areas containing users or activities while using lower-quality processing for static or less important areas. This resolves the contradiction by maintaining focus on dynamic areas without requiring full-scene high-resolution processing.
2Measurement precision
If the system increases pixel density in areas of interest, then image detail improves, but processing load and memory requirements worsen
Solution Approach 1:
The patent implements dynamic adjustment of pixel density and processing resolution based on real-time scene analysis. The system continuously identifies regions of interest and dynamically allocates processing resources, increasing pixel density only in areas containing users or activities while maintaining lower density elsewhere. This dynamic approach allows high measurement precision in critical areas without imposing excessive processing load system-wide.
Solution Approach 2:
The patent applies partial action by processing only the necessary portions of the scene at high detail levels. Instead of processing the entire scene at maximum resolution, the system identifies and processes only the regions containing relevant information (users, gestures, activities) at high pixel density, while using reduced processing for other areas. This reduces overall processing load while maintaining sufficient image detail where needed.
3Measurement precision
If the system focuses on small dynamic areas, then gesture recognition accuracy improves, but coverage of the entire field of view worsens
Solution Approach 1:
The patent segments the field of view into multiple zones with different processing priorities. Regions containing users or detected activities are segmented as high-priority areas receiving enhanced focus and processing, while other areas are segmented as lower-priority regions maintaining broader coverage at reduced detail. This segmentation enables accurate gesture recognition in dynamic areas while preserving overall field of view coverage through multi-resolution processing.
Solution Approach 2:
The patent resolves the coverage contradiction by adding a spatial resolution dimension to the processing strategy. The system processes different spatial regions at different resolution levels simultaneously, creating a multi-scale representation of the scene. This allows high-resolution processing of small dynamic areas for accurate gesture recognition while maintaining low-resolution coverage of the entire field of view, effectively utilizing multiple dimensions of spatial detail.
Data Source
AI summary
A system and method are disclosed for selectively focusing on certain areas of interest within an imaged scene to gain more image detail within those areas. In general, the present system identifies areas of interest from received image data, which may for example be detected areas of movement within the scene. The system then focuses on those areas by providing more detail in the area of interest. This may be accomplished by a number of methods, including zooming in on the image, increasing pixel density of the image and increasing the amount of light incident on the object in the image.