UAV Camera Network Dynamic Positioning for 3D Scene Coverage
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Solution Overview
Problem
Conventional multiple-camera network systems face limitations in providing optimal coverage of predefined areas, especially when stationary cameras are not suitably placed, and require lengthy calibration processes, which can hinder efficient capture and processing of static and motion scenes.
Innovation Solution
A system and method utilizing a network of unmanned aerial vehicles (UAVs) equipped with imaging devices that dynamically adjust their location and orientation to capture images of static and moving objects, synchronizing these images for 3D reconstruction, and calibrating imaging devices using focal lens information and calibration objects to enhance coverage and reduce calibration time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If stationary cameras are used in multiple-camera network systems, then the system structure is simple and stable, but the coverage of predefined areas is insufficient and placement flexibility is limited
Solution Approach 1:
The patent introduces movable cameras (UAVs) that can dynamically adjust their positions and orientations to achieve optimal coverage of predefined areas. The movable camera system transitions from static to dynamic deployment, allowing flexible repositioning to capture scenes from multiple angles and locations, thereby significantly expanding the effective coverage area without permanently increasing system complexity through fixed infrastructure.
2Measurement precision
If conventional calibration processes are used for multiple cameras, then measurement accuracy is achieved, but the calibration time is lengthy and reduces productivity
Solution Approach 1:
The patent implements preliminary calibration actions by pre-positioning calibration objects in the scene before actual camera calibration begins. The system automatically detects these pre-placed calibration objects and uses them to initiate the calibration process, eliminating the need for time-consuming manual calibration procedures. This preliminary setup enables rapid automated calibration while maintaining high measurement precision through the use of known calibration object geometries and positions.
Solution Approach 2:
The calibration system performs self-calibration by automatically detecting calibration objects in the captured images and computing camera parameters without external intervention. The algorithm autonomously identifies calibration patterns, calculates intrinsic and extrinsic parameters, and adjusts camera configurations based on detected features, thereby achieving both high accuracy and fast calibration speed through automated self-service calibration processes.
3Area of stationary object
If more cameras are added to improve coverage, then the coverage area increases, but the calibration time and processing complexity increase
Solution Approach 1:
The patent uses virtual camera models and digital twins to represent physical cameras in the calibration process. Instead of calibrating each physical camera individually through time-consuming procedures, the system creates virtual copies that can be rapidly calibrated using computational algorithms. This copying approach allows multiple camera views to be integrated efficiently, expanding coverage area while minimizing calibration time through virtual representation and parallel processing of camera parameters.
Data Source
AI summary
Various aspects of a system and method for utilization of multiple-camera network to capture static and/or motion scenes are disclosed herein. The system comprises a plurality of unmanned aerial vehicles (UAVs). Each of the plurality of UAVs is associated with an imaging device configured to capture a plurality of images. A first UAV of the plurality of UAVs comprises a first imaging device configured to capture a first set of images of one or more static and/or moving objects. The first UAV is configured to receive focal lens information, current location and current orientation from one or more imaging devices. A target location and a target orientation of each of the one or more imaging devices are determined. Control information is communicated to the one or more other UAVs to modify the current location and current orientation to the determined target location and orientation of each of the one or more imaging devices.