Merging Aerial Imagery and Heightmap Data for Structure Detection
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Solution Overview
Problem
Detecting property structures in aerial imagery is challenging due to the difficulty in perceiving structures in detail, especially from overhead distances, and the potential for human error in manual inspections.
Innovation Solution
A computer vision system that merges aerial imagery with heightmap data to create a combined image, using a convolutional neural network to detect structures, generate bounding boxes or polygons, and assign structure classifications, while determining geographic locations of structures using 2D spatial information and depth data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection by human operators is used to detect structures in aerial imagery, then human judgment and flexibility are applied, but human error and bias occur leading to inaccurate assessment
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated computer vision system that processes aerial imagery and heightmap data. The system uses algorithms to automatically detect, classify, and measure structures, eliminating human operators from the direct inspection process while maintaining or improving assessment accuracy through consistent, objective analysis of the data.
2Measurement precision
If aerial imagery alone is used to detect structures, then simplicity of data collection is maintained, but detection accuracy deteriorates due to inability to perceive structures in detail from overhead distances
Solution Approach 1:
The patent merges two different data sources - aerial imagery and heightmap data - into a unified analysis framework. The aerial imagery provides visual context and texture information, while the heightmap data provides precise elevation and depth information. By combining these complementary data sources, the system achieves superior structure detection accuracy that neither source could provide alone, despite the increased complexity of processing multiple data types.
3Productivity
If multiple human operators are used to inspect properties, then comprehensive coverage is attempted, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The patent implements a self-service automated system that independently performs the entire inspection process without requiring multiple human operators. The computer vision system automatically processes aerial imagery and heightmap data, detects structures, classifies them by type and material, and generates assessment reports. This single automated system replaces the cumbersome multi-operator manual process, dramatically improving productivity while reducing the time required for comprehensive property inspections.
Data Source
AI summary
Computer vision systems and methods for detecting structures using aerial imagery and heightmap data are provided. The system receives aerial imagery and at least one heightmap, and merges the aerial imagery and the heightmap to create a combined image. The system determines one or more structures of the land property based at least in part on the combined image and a computer vision model, which can detect one or more objects in the combined image. The system can generate and place a bounding box or a polygon around each of the detected objects, and generate and assign a structure classification to the bounding box or the polygon to indicate the structure of the object. The system can also determine a geographic location of each structure using the two-dimensional (2D) spatial information of the aerial imagery and the depth information of the heightmap.