Window View Openness Index Calculation Using Distance Adjustment

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Solution Overview

Problem

Existing methods for quantifying window view openness lack accuracy due to the absence of distance information, which is crucial for differentiating views with similar sky layer proportions but varying distances to landscape elements.

Innovation Solution

A system and method that utilize window view images to compute a Window View Openness Index (WVOI) by extracting the proportion of distant view layers and measuring close-range view layer distances, then applying an openness adjustment factor based on these distances.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If view photography is used to capture window views, then data acquisition cost is reduced and realism is improved, but distance information is lost and measurement precision deteriorates

Engineering Contradiction:

Improvewindow view openness quantification accuracyVSAvoiddistance information

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent introduces an intermediary computational layer that processes view images and combines them with distance data from multiple sources (LiDAR, photogrammetry, or manual measurement) to reconstruct the complete window view openness index, thereby recovering the lost distance information while maintaining the cost-effectiveness of view photography

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent merges two previously separate data sources: view images (providing visual content and sky layer proportion) and distance measurements (providing spatial information). By combining these datasets through a unified computational framework, the system achieves both the realism of photography and the precision of distance-aware measurement

Inventive Principle:

Principle #5Merging (Combining)

2Productivity

If sky layer proportion is extracted from view images, then computation is simplified and efficiency is improved, but view openness differentiation capability deteriorates

Engineering Contradiction:

Improvecomputation efficiencyVSAvoidview openness differentiation accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent segments the window view openness computation into two independent components: sky layer proportion extraction (computational efficiency) and distance-based openness adjustment (differentiation capability). Each component can be processed separately using optimized algorithms, then combined to produce the final comprehensive openness index

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250173916A1System and methods for quantifying and calculating window view openness indexes

Publication Date: 2025.05.29 THE UNIVERSITY OF HONG KONG

AI summary

A method and systems for quantifying and calculating window view openness indexes based on window view photos and view distances are provided. The method includes generating a window view image by an image capturing device; computing a distant view layer proportion; measuring and computing a close-range view layer distance; computing a view distance-based openness adjustment factor (OAF); and computing a window view openness index (WVOI). The computing of a distant view layer proportion may include extracting a proportion of a distant layer of the window view image as a basic factor to measure view openness. The OAF is summarized from view distances computed in the step of measuring and computing a close-range view layer distance. The WVOI is calculated based on the proportion of distant view layer and the OAF from the close-range view layer distance.