Stereoscopic Camera Rig with Light Field Depth Mapping
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Solution Overview
Problem
Current camera systems face challenges in capturing high-quality stereoscopic image content and environmental measurements simultaneously, particularly in real-time, due to the complexity of computational processing and the need for multiple cameras oriented differently, which affects the quality and practicality of 3D content generation and streaming.
Innovation Solution
A camera rig equipped with multiple pairs of cameras, including stereoscopic and light field cameras, is used to capture left and right eye images in parallel, allowing for synchronized image capture in multiple directions, enabling real-time streaming and updating of environmental models with depth information, thus facilitating high-definition, high-dynamic-range, 360-degree panoramic video capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple cameras oriented in different directions are used to capture images, then the camera rig need not simulate the human visual system, but the computational processing complexity increases and the quality of 3D content generation deteriorates
Solution Approach 1:
The camera system is divided into multiple independent camera units, each capturing images from its own oriented perspective. This segmentation allows each camera to be optimized for its specific viewing angle while the overall system integrates these segmented views through computational processing to generate stereoscopic content.
Solution Approach 2:
The system transitions from capturing images in a single plane to capturing images in multiple spatial dimensions by orienting cameras in different directions. This multi-dimensional capture approach enables comprehensive environmental coverage while maintaining the ability to generate realistic 3D stereoscopic views through computational synthesis.
2Adaptability or versatility
If computational processing is used to generate stereoscopic image pairs from cameras facing different directions, then the camera rig need not simulate the human visual system, but the time required for generating image pairs increases
Solution Approach 1:
Multiple cameras capture images from different directions simultaneously in advance, storing these pre-captured images for later processing. This preliminary capture action enables the system to process and generate stereoscopic image pairs more efficiently, as the raw image data is already available and does not need to be captured in real-time during the actual event.
Solution Approach 2:
The system continuously captures images from multiple camera orientations throughout the event duration, maintaining uninterrupted image acquisition. This continuous capture ensures that sufficient image data is accumulated for generating real-time stereoscopic views, reducing the time needed for post-processing and enabling live streaming applications.
3Adaptability or versatility
If cameras are arranged in a configuration different from human eye spacing and orientation, then the camera rig can capture environmental content, but the generated 3D content quality deteriorates
Solution Approach 1:
The system varies the spatial parameters (position, orientation, and spacing) of multiple camera units to capture images from diverse perspectives. By adjusting these parameters, the system can generate stereoscopic image pairs that accurately represent the environment while accommodating different camera configurations, maintaining high 3D content quality through computational processing.
Solution Approach 2:
The system creates multiple virtual camera views by computationally synthesizing images from the actual camera captures. This copying process generates stereoscopic image pairs that replicate the appearance of scenes as they would be seen from human eye positions, even though the physical cameras are arranged differently, thus preserving 3D content quality.
4Ease of manufacture
If static environmental models are used, then the model can be pre-generated, but the ability to reflect real-time environmental changes during events is lost
Solution Approach 1:
The system performs preliminary capture of environmental images from multiple camera orientations before the actual event or in advance. These pre-captured images serve as the foundation for generating initial environmental models that can be quickly updated in real-time, combining the efficiency of pre-processing with the adaptability of real-time changes.
Solution Approach 2:
The system continuously updates environmental models by incorporating new image data captured during events. This feedback mechanism allows the model to reflect real-time environmental changes while maintaining the efficiency of pre-generated model structures. The updated models can be immediately applied to enhance the realism of virtual reality experiences during live events.
Data Source
AI summary
A camera rig including one or more stereoscopic camera pairs and/or one or more light field cameras are described. Images are captured by the light field cameras and stereoscopic camera pairs are captured at the same time. The light field images are used to generate an environmental depth map which accurately reflects the environment in which the stereoscopic images are captured at the time of image capture. In addition to providing depth information, images captured by the light field camera or cameras is combined with or used in place of stereoscopic image data to allow viewing and/or display of portions of a scene not captured by a stereoscopic camera pair.