Apple inc. (20240096013). SINGLE-PASS OBJECT SCANNING simplified abstract
Contents
- 1 SINGLE-PASS OBJECT SCANNING
SINGLE-PASS OBJECT SCANNING
Organization Name
Inventor(s)
Rafael Felipe Veiga Saracchini of Berlin (DE)
Tobias Rick of Mountain View CA (US)
Zachary Z. Becker of Issaquah WA (US)
SINGLE-PASS OBJECT SCANNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240096013 titled 'SINGLE-PASS OBJECT SCANNING
Simplified Explanation
The patent application describes a method for generating a three-dimensional (3D) model based on a selected subset of images and depth data corresponding to each image.
- Acquiring sensor data during movement of a device in a physical environment, including capturing images via a camera on the device.
- Selecting a subset of images based on assessing them for motion-based defects using device motion and depth data.
- Generating a 3D model of an object based on the selected subset of images and depth data.
Potential Applications
This technology could be used in various industries such as:
- Augmented reality
- Virtual reality
- Robotics
- 3D scanning and modeling
Problems Solved
- Efficient generation of 3D models
- Reduction of motion-based defects in the final model
- Improved accuracy in object reconstruction
Benefits
- Enhanced visualization of objects in 3D
- Increased efficiency in creating 3D models
- Better quality and accuracy of 3D reconstructions
Potential Commercial Applications
- 3D scanning and printing services
- Virtual reality gaming
- Architectural and engineering design
- Medical imaging and diagnostics
Possible Prior Art
One possible prior art could be the use of structured light or laser scanning techniques for 3D modeling. Another could be the use of photogrammetry for generating 3D models from images.
What are the specific motion-based defects that are assessed in the images?
The specific motion-based defects that are assessed in the images include blurring, distortion, and misalignment caused by the movement of the device during image capture.
How does the depth data contribute to the generation of the 3D model?
The depth data provides additional spatial information that helps in accurately reconstructing the object in three dimensions. By combining the depth data with the selected subset of images, the 3D model can capture the shape and structure of the object more effectively.
Original Abstract Submitted
various implementations disclosed herein include devices, systems, and methods that generates a three-dimensional (3d) model based on a selected subset of the images and depth data corresponding to each of the images of the subset. for example, an example process may include acquiring sensor data during movement of the device in a physical environment including an object, the sensor data including images of a physical environment captured via a camera on the device, selecting a subset of the images based on assessing the images with respect to motion-based defects based on device motion and depth data, and generating a 3d model of the object based on the selected subset of the images and depth data corresponding to each of the images of the selected subset.
