Mobile Camera 3D Modeling via Motion Tracking
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Solution Overview
Problem
Existing systems for capturing and reproducing anatomical models require specialized hardware, such as structured light sources or lasers, which are costly and complex, limiting their accessibility and usability in fields like surgery, clothing, and 3D printing.
Innovation Solution
A method using a mobile phone with a camera and accelerometer sensor to capture 3D models of products or body parts without the need for depth sensors, by performing motion tracking and understanding the environment, and then projecting the product into the environment for augmented or virtual reality display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specialized hardware such as structured light sources or lasers is used to capture 3D models, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts the depth sensing capability from specialized hardware and implements it through software algorithms running on standard mobile device cameras. The system removes the need for separate depth sensors by using monocular vision techniques that process regular 2D images to infer 3D spatial information through computational methods.
Solution Approach 2:
The system creates a virtual copy of the specialized 3D scanning functionality using software algorithms that simulate depth perception. Instead of requiring physical depth sensors, the patent uses image processing techniques to generate depth maps and 3D models from standard camera images, effectively copying the functional capability without the hardware overhead.
2Measurement precision
If specialized hardware such as structured light sources or lasers is used to capture 3D models, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent replaces expensive, specialized 3D scanning hardware with inexpensive, widely available mobile device cameras. By using standard components that consumers already possess, the system eliminates the need for costly proprietary equipment while maintaining acceptable measurement precision through advanced software processing.
Solution Approach 2:
The patent substitutes mechanical/optical depth sensing mechanisms (structured light projectors, laser scanners) with computational image processing methods. The system uses algorithms to infer depth and spatial relationships from 2D images, replacing physical measurement mechanisms with mathematical computations that run on standard mobile processors.
3Measurement precision
If multiple image capture devices are used to estimate depth, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the depth estimation task into multiple computational stages performed by software algorithms. Instead of requiring multiple physical cameras, the system divides the processing into steps such as feature detection, epipolar geometry computation, and depth map generation, all executed sequentially on a single device's processor.
Solution Approach 2:
The patent introduces computational algorithms as intermediaries that translate 2D image data into 3D spatial information. These software mediators process the relationship between multiple images taken from different angles and synthesize depth perception without requiring simultaneous multi-camera hardware.
Data Source
AI summary
Systems and methods are disclosed for recommending products or services by receiving a three-dimensional (3D) model of one or more products; performing motion tracking and understanding an environment with points or planes and estimating light or color in the environment; and projecting the product in the environment.