Crowdsourced Holographic View Generation Without Camera Arrays
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Solution Overview
Problem
Capturing content for lightfield or holographic displays requires expensive setups with multiple depth cameras or arrays of cameras, making it cost-prohibitive.
Innovation Solution
Utilize crowdsourcing techniques with multiple imaging devices at different locations to capture and align images, generating a 3D model that can be used to render holographic displays without the need for expensive equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple depth cameras or arrays of cameras are used to capture lightfield content, then the quality of holographic display is improved, but the cost and device complexity increase significantly
Solution Approach 1:
The patent creates a digital 3D model (virtual copy) of the physical scene using images from multiple crowd-sourced devices. This digital twin allows holographic rendering without requiring physical arrays of cameras, thereby reducing device complexity while maintaining display quality
Solution Approach 2:
The patent introduces a server as an intermediary that collects images from multiple crowd-sourced devices, processes them into a 3D model, and delivers rendered holographic content to display devices. This intermediary architecture eliminates the need for direct peer-to-peer camera arrays at the user end
2Measurement precision
If multiple depth cameras or arrays of cameras are used to capture lightfield content, then the depth accuracy is improved, but the cost becomes prohibitive
Solution Approach 1:
The patent replaces expensive, specialized lightfield camera arrays with multiple inexpensive, off-the-shelf imaging devices (smartphones, webcams) that can be crowd-sourced. These cheap devices collectively provide sufficient data for accurate 3D modeling without the prohibitive cost of dedicated holographic capture equipment
Solution Approach 2:
The patent combines images from multiple independent, low-cost imaging devices to achieve the depth accuracy previously requiring expensive specialized equipment. By merging data from crowd-sourced devices through a centralized server, the system achieves high measurement precision using inexpensive components
3Ease of operation
If traditional cameras are used to capture scenes, then the simplicity of equipment is maintained, but the ability to capture lightfield information is lost
Solution Approach 1:
The patent transitions from 2D image capture by traditional cameras to 3D spatial modeling by collecting images from multiple devices at different positions and orientations. This dimensional expansion allows reconstruction of lightfield information (depth, volume, spatial relationships) while maintaining simplicity of individual capture devices
Solution Approach 2:
The patent segments the lightfield capture task across multiple independent imaging devices positioned at different locations around the scene. Each device captures a portion of the lightfield information from its specific viewpoint, and the server integrates these segmented views into a complete 3D model, preserving both equipment simplicity and lightfield information
Data Source
AI summary
Method, device, and non-transitory storage medium for generating crowdsourced holographic views are provided. The method may include receiving one or more images of a same scene from one or more imaging devices, where each of the one or more imaging devices is at different locations. The method may further include generating a 3D model of the same scene based on the one or more images and streaming immersive media for rendering a holographic display of the same scene based on the 3D model based on determining that a display device is capable of displaying immersive media.