Virtual Viewpoint Imaging Control for High-Interest Region Capture
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Solution Overview
Problem
Existing systems struggle to generate high-resolution virtual viewpoint images efficiently, particularly in dynamic environments like a soccer stadium, where viewer interest points need to be accurately captured and imaged with multiple cameras.
Innovation Solution
An information processing apparatus that generates control signals for multiple imaging devices to adjust position, direction, focal length, and imaging conditions to capture high-resolution virtual viewpoint images, focusing on regions of high viewer interest, using machine learning for image recognition and calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple imaging apparatuses are used to capture virtual viewpoint video data from multiple directions, then the completeness of viewpoint coverage is improved, but the system complexity and data processing load increase
Solution Approach 1:
The system divides the viewpoint capture task into multiple segments, with each imaging apparatus responsible for capturing video data from a specific direction. This segmentation allows comprehensive viewpoint coverage while managing system complexity by distributing the capture function across multiple independent units.
Solution Approach 2:
The imaging apparatuses are designed with universal functionality to capture video data that can serve multiple purposes: both as source material for virtual viewpoint generation and as reference for interest point detection. This multi-functionality reduces the need for specialized equipment for each function.
2Adaptability or versatility
If virtual viewpoint video data is generated and stored for multiple directions, then the availability of search results is improved, but the storage requirements and data management complexity increase
Solution Approach 1:
The system extracts only the essential virtual viewpoint video data and interest point information needed for search operations, rather than storing all raw video data from multiple directions. This extraction approach maintains search result availability while significantly reducing storage requirements.
Solution Approach 2:
The system performs preliminary processing of video data to generate virtual viewpoint representations and detect interest points before storage. This preliminary action organizes data in a compact, search-ready format that reduces storage volume while maintaining quick retrieval capability.
3Measurement precision
If the imaging apparatus adjusts position and imaging direction to capture high-resolution images of interest regions, then the image quality is improved, but the response time and system latency increase
Solution Approach 1:
The system performs preliminary detection of interest points in the video data to identify regions requiring high-resolution capture. By pre-identifying these regions, the imaging apparatus can quickly adjust to capture only the necessary high-resolution data, reducing overall response time while maintaining image quality for critical areas.
Solution Approach 2:
The imaging apparatus applies different quality levels to different regions of interest. High-resolution capture is applied only to detected interest points and surrounding regions, while other areas use standard resolution. This local quality approach maintains response time by avoiding full-scene high-resolution capture while ensuring image quality where needed.
4Productivity
If the system generates control signals to adjust imaging apparatus in real-time, then the responsiveness to viewer interest is improved, but the computational load and processing time increase
Solution Approach 1:
The system extracts only the critical interest point information from video data to generate control signals, rather than processing entire video frames. This extraction approach maintains real-time responsiveness by reducing computational load to essential features while still enabling dynamic adjustment of imaging apparatus.
Solution Approach 2:
The system performs partial processing by focusing computational resources only on detected interest points and their immediate surroundings, rather than analyzing entire video scenes. This partial action approach achieves real-time responsiveness with reduced computational load by applying intensive processing only where necessary.
Data Source
AI summary
An information processing apparatus includes a processor capable of generating a virtual viewpoint image based on a plurality of captured images acquired by imaging with a plurality of imaging apparatuses, and a memory built in or connected to the processor. The processor generates a control signal for a control target imaging apparatus among the plurality of imaging apparatuses based on at least one of an instruction given from an outside regarding generation of the virtual viewpoint image or a subject.