Automated 3D Matrix Framing Using Range Camera Depth Data
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Solution Overview
Problem
Current methods for generating 3D models from objects are inefficient and require manual intervention, leading to high data wastage and reduced image quality due to lack of automated framing and depth information utilization.
Innovation Solution
A 3D imaging system that automatically adjusts camera settings based on depth information and operational constraints to capture a matrix of images, minimizing whitespace and optimizing image quality by determining appropriate fields of view and overlap for each camera.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual intervention is used for generating 3D models, then flexibility and control are improved, but efficiency and productivity deteriorate
Solution Approach 1:
The system performs self-service by automatically determining field of view boundaries and camera parameters using depth information from the range camera. The automated framing system calculates the object boundaries and configures the camera array without requiring manual intervention, thereby maintaining operational flexibility while dramatically improving productivity
Solution Approach 2:
The system performs preliminary action by capturing depth information from the object using a range camera before the main imaging process. This preliminary depth data is then used to pre-calculate the optimal field of view and camera configuration, enabling the subsequent high-speed automated capture phase to proceed efficiently without manual setup
2Device complexity
If conventional imaging methods are used without depth information, then device complexity is reduced, but data wastage increases and image quality deteriorates
Solution Approach 1:
The range camera performs preliminary scanning to obtain depth information about the object's shape and boundaries. This preliminary action enables the system to calculate precise field of view boundaries before the main imaging process, ensuring that subsequent images capture only relevant data and eliminate whitespace, thereby reducing data wastage without significantly increasing overall system complexity
Solution Approach 2:
The system replaces manual mechanical adjustment of camera parameters with automated computational methods. Depth information from the range camera is processed algorithmically to determine optimal field of view and camera configuration, substituting manual mechanical setup with automated optical and computational processes that reduce data wastage while maintaining reasonable system complexity
3Productivity
If automated framing using depth information is implemented, then image quality and productivity are improved, but device complexity increases
Solution Approach 1:
The imaging system is segmented into distinct functional modules: a range camera for depth acquisition, a control system for processing depth information and calculating field of view boundaries, and an array of cameras for image capture. This segmentation allows the automated framing functionality to be added as a modular enhancement rather than requiring complete system redesign, thereby improving productivity while managing device complexity through functional decomposition
Solution Approach 2:
The control system acts as an intermediary between the range camera and the imaging camera array. It receives depth information from the range camera, processes this data to determine optimal field of view and camera parameters, and then configures the imaging system accordingly. This intermediary layer enables automated framing and high-speed capture without requiring direct complex integration between all system components, thereby managing overall system complexity
4Adaptability or versatility
If manual configuration of camera parameters is used, then adaptability to specific cases is improved, but time consumption increases
Solution Approach 1:
The system performs self-service by automatically adapting to different objects through automated field of view calculation. When an object is placed in the scene, the range camera captures its depth profile, the control system processes this data to determine optimal imaging parameters, and the camera array is automatically configured accordingly. This self-service capability maintains full adaptability to different object shapes and sizes while eliminating manual setup time
Solution Approach 2:
The range camera performs preliminary scanning of the object to obtain depth information before the main imaging process begins. This preliminary action allows the system to pre-calculate the optimal field of view and camera configuration specific to each object, enabling rapid adaptation to different cases without requiring manual reconfiguration. The preliminary depth data serves as the basis for automated parameter optimization
Data Source
AI summary
Described herein are a system and methods for generating 3D models using imaging data obtained from an array of camera devices. In embodiments, the system may determine a depth or range between an object and the array of camera device. Based on this depth information, the system may automatically identify appropriate framing information for that array of camera devices based on operational constraints. One or more properties of the camera devices in the array of camera devices may then be adjusted in order to obtain image information in accordance with the identified framing information. The object may then be rotated in accordance with the operational constraints and the process may be repeated until a full set of images has been obtained.