Multi-Viewpoint Image Generation for 3D Modeling
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Solution Overview
Problem
Current methods for generating a three-dimensional model or training a classifier for arbitrary view-point object recognition lack an efficient way to acquire a sufficient number of images from various view points, especially for complex structures, and do not provide a clear method for densely arranging view points to capture detailed images.
Innovation Solution
An information processing apparatus and method that calculates relative positions and orientations of an imaging unit with respect to an object from multiple view points, identifies missing view points, and generates images for those points, allowing for the display and subsequent imaging to achieve a multi-view-point image composed of images from evenly captured views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a great number of images are acquired from various view points to improve three-dimensional model accuracy and classifier learning, then the quality of object recognition and modeling is improved, but the complexity of the imaging process and the time required to capture all necessary images increase
Solution Approach 1:
The system performs preliminary actions by calculating all necessary view points and imaging sequences before actual image capture begins. The missing viewpoint calculation unit pre-determines which viewpoints need to be captured, and the imaging sequence determination unit pre-plans the optimal capture order, allowing the imaging process to proceed efficiently without unnecessary delays
Solution Approach 2:
The system implements feedback mechanisms where the acquired images are continuously evaluated against the target viewpoint distribution. The missing viewpoint calculation unit identifies gaps in the captured data, and this information feeds back into the imaging sequence determination to prioritize capturing the most critical missing viewpoints first, progressively improving model accuracy
2Manufacturing precision
If view points are densely arranged to capture detailed images of complex structures, then the imaging detail and completeness are improved, but the number of images required and the processing complexity increase
Solution Approach 1:
The system applies local quality by determining different viewpoint densities for different regions of the object. Complex structures and critical features are captured with higher viewpoint density, while simpler regions use lower density. The missing viewpoint calculation unit identifies which specific areas require detailed imaging based on the object's geometric complexity
Solution Approach 2:
The system performs partial action by capturing only the essential viewpoints needed for adequate object representation rather than uniformly dense sampling from all directions. The imaging sequence determination unit prioritizes capturing viewpoints that provide the most information gain, avoiding redundant captures
3Ease of operation
If markers are used as reference for viewpoint positioning to simplify the imaging setup, then the ease of operation is improved, but the loss of information about natural object features increases
Solution Approach 1:
The system uses markers as intermediary objects that facilitate the measurement process without becoming part of the final object model. The markers serve as temporary reference points for calculating relative positions and orientations, but are excluded from the three-dimensional model and classifier training data, thus acting as a mediator that enables measurement while preserving object feature integrity
Data Source
AI summary
A multi view-point image composed of a great number of images according to a shape of an object is generated or an information processing method used for generating a three-dimensional model or performing image processing of arbitrary view-point object recognition is provided, and based on a plurality of captured images obtained by imaging of the object from a plurality of view points by an imaging means, a relative position and orientation with respect to the object relative to the imaging means for each of the plurality of view points is calculated, and based on the calculated plurality of relative positions and orientations, a missing position and orientation of the imaging means in a direction in which imaging by the imaging means is missing is calculated, and an image used for displaying the calculated missing position and orientation on a display means is generated.