IP Library › Granted Patent US 12,309,333
Granted Patent B2
US 12,309,333 · App. 17/547,751 · Granted May 20, 2025

Method and apparatus for scanning and printing a 3D object

Inventors: Alexander Ilic (Zurich, CH); Benedikt Koeppel (Zurich, CH)
Assignee: Magic Leap, Inc.
H04N1/00827B33Y50/00G01B11/24G06T7/55G06T7/74G06T15/04G06T17/20G06T19/20H04N13/211H04N13/221H04N13/271H04N13/275G06T2200/08G06T2207/10016G06T2207/10028G06T2207/20076G06T2207/30244G06T2219/2021
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Quick Facts
Patent No.
US 12,309,333
App. No.
17/547,751
Filed
Dec 10, 2021
Granted
May 20, 2025
Kind
B2
Examiner
HOANG, PETER
Art Unit
2616
USPC
358/450
Abstract

A smartphone may be freely moved in three dimensions as it captures a stream of images of an object. Multiple image frames may be captured in different orientations and distances from the object and combined into a composite image representing an three-dimensional image of the object. The image frames may be formed into the composite image based on representing features of each image frame as a set of points in a three dimensional depth map. Coordinates of the points in the depth map may be estimated with a level of certainty. The level of certainty may be used to determine which points are included in the composite image. The selected points may be smoothed and a mesh model may be formed by creating a convex hull of the selected points. The mesh model and associated texture information may be used to render a three-dimensional representation of the object on a two-dimensional display. Additional techniques include processing and formatting of the three-dimensional representation data to be printed by a three-dimensional printer so a three-dimensional model of the object may be formed.

Claims (42)

1. A portable electronic device, comprising:

a camera;

at least one processor, configured to:

process a plurality of images acquired with the camera to form a representation of an object depicted in the plurality of images, wherein the representation indicates a surface of the object in three-dimensional space, and wherein the processing comprises:

forming multiple localized point clouds, each localized point cloud comprising probabilities associated with respective points in the localized point cloud indicative of a probability that the representation accurately indicates a location of a first feature of a plurality of features;

fusing the localized point clouds into a combined point cloud;

adjusting one or more points in the combined point cloud to reduce inconsistency; and

smoothing the combined point cloud based at least in part on the probabilities associated with the localized point clouds.

2. The portable electronic device of claim 1 , wherein the at least one processor is configured to compute probabilities associated with respective points in a localized point cloud at least in part by determining a probability that a feature depicted in a first image of the plurality of images and a feature depicted in a second image of the plurality of images are both the first feature.

3. The portable electronic device of claim 2 , wherein determining the probability that the feature depicted in the first image and the feature depicted in the second image are both the first feature comprises performing cross-correlation to identify similar regions of the object in the first image and the second image.

4. The portable electronic device of claim 1 , wherein the at least one processor is configured to compute probabilities associated with respective points in a localized point cloud at least in part using geometric analysis to identify locations of specific features of the plurality of features depicted in more than one of the plurality of images.

5. The portable electronic device of claim 4 , comprising a sensor for detecting motion of the portable electronic device, wherein the at least one processor is configured to form the localized point clouds at least in part by analyzing motion of the portable electronic device, detected by the sensor, between acquisition of one of the plurality of images and acquisition of another of the plurality of images.

6. The portable electronic device of claim 1 , wherein the at least one processor is configured to form each one of the localized point clouds at least in part by:

forming a first version of the one localized point cloud; and

using probability to determine whether to update the first version.

7. The portable electronic device of claim 6 , wherein using probability to determine whether to update the first version comprises:

identifying a feature of the object that is not indicated in the first version and that is depicted in a new image of the plurality of images, acquired after the first version was formed; and

determining a probability that the feature is accurately located in the new image.

8. The portable electronic device of claim 7 , wherein the at least one processor is configured to update the first version if the determined probability that the feature is accurately located in the new image satisfies a predetermined threshold.

9. The portable electronic device of claim 1 , wherein the at least one processor is configured to:

compute a surface description from the smoothed combined point cloud by calculating a convex hull for one or more points in the smoothed combined point cloud; and

store the surface description as a three-dimensional file.

10. The portable electronic device of claim 9 , wherein the at least one processor is configured to add texture information to the surface description.

11. A method for use in a portable electronic device comprising at least one processor, the method comprising acts of:

processing, by the at least one processor, a plurality of images acquired by the portable electronic device to form a representation of an object depicted in the plurality of images, the representation indicating respective locations of a plurality of features of the object in three-dimensional space, the processing comprising:

forming multiple localized point clouds, each localized point cloud comprising probabilities associated with respective points in the localized point cloud indicative of a probability that the representation accurately indicates a location of a first feature of the plurality of features;

fusing the localized point clouds into a combined point cloud;

adjusting one or more points in the combined point cloud to reduce inconsistency; and

smoothing the combined point cloud based at least in part on the probabilities associated with the localized point clouds.

12. The method of claim 11 , wherein computing probabilities associated with respective points in a localized point cloud comprises determining a probability that a feature depicted in a first image of the plurality of images and a feature depicted in a second image of the plurality of images are both the first feature.

13. The method of claim 12 , wherein determining the probability that the feature depicted in the first image and the feature depicted in the second image are both the first feature comprises performing cross-correlation to identify similar regions of the object in the first image and the second image.

14. The method of claim 11 , wherein forming localized point clouds comprises using geometric analysis to identify locations of specific features of the plurality of features depicted in more than one of the plurality of images.

15. The method of claim 11 , wherein forming localized point clouds comprises analyzing motion of the portable electronic device between acquisition of one of the plurality of images and another of the plurality of images.

16. The method of claim 11 , wherein forming each one of the localized point clouds comprises forming a first version of one localized point cloud and using probability to determine whether to update the first version.

17. The method of claim 16 , wherein using probability to determine whether to update the first version comprises:

identifying a feature of the object that is not indicated in the first version and that is depicted in a new image of the plurality of images, acquired after the first version was formed; and

determining a probability that the feature is accurately located in the new image.

18. The method of claim 17 , further comprising updating the first version if the determined probability that the feature is accurately located in the new image satisfies a predetermined threshold.

19. The method of claim 11 , further comprising:

computing a surface description from the smoothed combined point cloud by calculating a convex hull for one or more points in the smoothed combined point cloud; and

storing the surface description as a three-dimensional file.

20. The method of claim 19 , further comprising adding texture information to the surface description.

Assignments (6)
SECURITY INTEREST Recorded Oct 31, 2025
From: MAGIC LEAP, INC.; MENTOR ACQUISITION ONE, LLC; MOLECULAR IMPRINTS, INC.
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 073439/0168 →
SECURITY INTEREST Recorded Oct 24, 2025
From: MAGIC LEAP, INC.; MENTOR ACQUISITION ONE, LLC; MOLECULAR IMPRINTS, INC.
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 073255/0581 →
MERGER Recorded Oct 3, 2022
From: ML NETHERLANDS C.V.
To: MR INTERNATIONAL HOLDING LLC
Reel/Frame 061290/0365 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 3, 2022
From: MR INTERNATIONAL HOLDING LLC
To: MAGIC LEAP, INC.
Reel/Frame 061290/0606 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 18, 2022
From: DACUDA AG
To: ML NETHERLANDS C.V.
Reel/Frame 059048/0287 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 18, 2022
From: ILIC, ALEXANDER; KOEPPEL, BENEDIKT
To: DACUDA AG
Reel/Frame 059306/0495 →
Continuity (5)
Continuation 16685983 · Nov 15, 2019
Continuation 15308959
Provisional Application 61992601 · May 13, 2014
Provisional Application 61992204 · May 12, 2014
Related Publication 20220103709A1 · Mar 31, 2022
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