Geospatial Image Graph for Drone Data Transmission
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 3D image construction from drone-captured images is time-consuming and inefficient, especially in remote areas with low bandwidth connections, leading to delays in data collection and analysis, which is critical for real-time monitoring and decision-making in industries like agriculture, construction, and disaster management.
Innovation Solution
A computer-implemented method that creates a graph from raw image frames captured by a moving camera, indexes them geographically, skips frames with significant overlap, identifies frames with interesting features, and combines them to form unique frames, which are then prioritized and transmitted, allowing for incremental 3D image construction and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all raw image frames are processed and transmitted to the cloud for 3D image construction, then complete and accurate analytics can be obtained, but data transmission time and processing time increase significantly
Solution Approach 1:
The patent extracts only the most essential and informative image frames from the complete set of captured frames. By identifying and selecting key frames that contain the most valuable information for 3D reconstruction, the system transmits a reduced subset rather than all frames, thereby reducing transmission time while maintaining analytics accuracy.
Solution Approach 2:
The patent applies partial action by transmitting only a portion of the captured image frames rather than the complete set. The selective transmission of key frames represents a partial subset that is sufficient for constructing accurate 3D images, eliminating the need to transmit excessive data while preserving measurement precision.
2Area of stationary object
If redundant image frames with high overlap are transmitted, then comprehensive coverage is achieved, but data transmission bandwidth is wasted
Solution Approach 1:
The patent extracts and identifies redundant frames that provide overlapping coverage of the same areas. By detecting and eliminating these redundant frames from the transmission set, the system maintains comprehensive survey coverage while significantly reducing bandwidth consumption that would be wasted on duplicate information.
Solution Approach 2:
The patent discards redundant image frames that provide overlapping or duplicate coverage of already-surveyed areas. By identifying frames with high overlap through graph analysis and discarding them from transmission, the system recovers valuable bandwidth while maintaining complete area coverage through the non-redundant frame set.
3Quantity of substance
If frames are selected based on interesting features only, then transmission data volume is reduced, but some areas may be undersampled
Solution Approach 1:
The patent segments the frame selection process into multiple criteria: identifying frames with interesting features, evaluating overlap with already-selected frames, and ensuring adequate spatial distribution. This segmented approach ensures that the reduced data volume still captures sufficient information across all survey areas to maintain 3D reconstruction quality.
Solution Approach 2:
The patent applies different selection criteria to different regions of the survey area. Areas with interesting features receive priority selection, while other areas are sampled based on spatial distribution requirements. This local quality approach ensures that data volume is reduced overall while maintaining adequate sampling in all regions for accurate 3D reconstruction.
Data Source
AI summary
A computer implemented method includes obtaining data for raw image frames captured by a moving camera. The raw image frames are indexed geographically, and a graph is created from the multiple raw image frames. The graph includes image frames as vertices and edges that represent image frames having overlapping image information. The method further includes skipping frames based on the amount of overlap, determining a frame having an interesting feature, using the graph to find additional raw image frames that have the interesting feature, combining multiple raw image frames to form a unique image frame, and transmitting the unique image frame.