3D Texture Image Generation via Camera Grouping and Priority Selection
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Solution Overview
Problem
Current technologies face limitations in displaying high-quality texture images of various viewpoints using a single multi-camera unit, as they are restricted by the coverage and quality of the images captured.
Innovation Solution
An image processing device that classifies multiple cameras into groups based on their positions and sets priorities for each group to select and transmit texture images necessary for generating 3-dimensional data, allowing for the generation of high-quality texture images from multiple viewpoints by utilizing a plurality of multi-camera units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single multi-camera unit is used to generate entire celestial sphere images, then the device complexity is reduced, but the image quality and visual field range are limited
Solution Approach 1:
The patent divides the camera system into multiple multi-camera units, each responsible for capturing images from specific positions. By segmenting the overall imaging task across multiple units with assigned priorities, the system achieves higher image quality and broader visual field coverage while maintaining manageable complexity through structured organization.
2Area of stationary object
If multiple cameras are used to expand visual field range, then the coverage is improved, but the device complexity increases
Solution Approach 1:
Cameras are divided into multiple groups based on their spatial positions, with each group assigned a priority level. This segmentation allows the system to manage complex multi-camera configurations through organized hierarchy, where higher-priority groups contribute more significantly to the final image composition.
Solution Approach 2:
Different camera groups are assigned different priorities based on their positional characteristics and contribution quality to the overall image. This allows the system to optimize image quality by weighting contributions from different locations, ensuring that regions captured by higher-quality or more strategically positioned cameras have greater influence.
3Area of stationary object
If cameras from different positions are combined to generate texture images, then the visual field range is expanded, but the image selection complexity increases
Solution Approach 1:
The patent segments cameras into priority-based groups and processes image selection group by group. This approach simplifies the overall selection complexity by breaking down the decision-making process into manageable stages, where images are selected and combined in a systematic order based on group priorities.
Solution Approach 2:
The system performs preliminary classification of cameras into priority groups before the actual image selection and combination process. This preliminary organization establishes a clear framework that guides subsequent image processing steps, reducing the complexity of real-time decision-making during texture image generation.
Data Source
AI summary
An image processing device and an image processing method in which a home server that reproduces a 3-dimensional image merely by transmitting a viewing range based on a viewing position and a visual line direction and requesting texture images. The texture images are necessary to generate a 3-dimensional image from a request content server. A content server that groups a plurality of multi-camera units for each of cameras included in the multi-camera unit, sets a priority of the cameras for each group on the basis of an evaluation value of disposition of the cameras in each group, and transmits image data of a surface of the selected cameras in accordance with the set priority and the group selected in accordance with a visual field range of a user to a home server.