REDUCING STRESSES IN THE PASSABLE WORLD MODEL IN AUGMENTED OR VIRTUAL REALITY SYSTEMS

• US 20170061688A1
• Filed: 05/07/2015
• Published: 03/02/2017
• Est. Priority Date: 04/18/2014
• Status: Active Grant

• Current Assignee: Magic Leap, Inc.
• Original Assignee: Magic Leap, Inc.
• Inventors: MILLER, Samuel A.
• Granted Patent: US 10,665,018 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A63F 13/56 Computing the motion of game characters with respect to other game characters, game objects or elements of the game scene, e.g. for simulating the behaviour of a group of virtual soldiers or for path finding
• CPC Class Codes: A63F 13/57 Simulating properties, behaviour or motion of objects in the game world, e.g. computing tyre load in a car race game A63F13/56 takes precedence
• CPC Class Codes: A63F 13/577 using determination of contact between game characters or objects, e.g. to avoid collision between virtual racing cars
• CPC Class Codes: G02B 2027/0138 comprising image capture systems, e.g. camera
• CPC Class Codes: G02B 2027/014 comprising information/image processing systems
• CPC Class Codes: G02B 2027/0178 Eyeglass type eyeglass details G02C
• CPC Class Codes: G02B 2027/0187 slaved to motion of at least a part of the body of the user, e.g. head, eye
• CPC Class Codes: G02B 27/0093 with means for monitoring data relating to the user, e.g. head-tracking, eye-tracking
• CPC Class Codes: G02B 27/0101 characterised by optical features G02B27/0172 takes precedence
• CPC Class Codes: G02B 27/017 Head mounted
• CPC Class Codes: G02B 27/0172 characterised by optical features
• CPC Class Codes: G02B 27/0179 Display position adjusting means not related to the information to be displayed
• CPC Class Codes: G06F 3/005 Input arrangements through a video camera
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• CPC Class Codes: G06F 3/012 Head tracking input arrangements
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G06F 3/014 Hand-worn input/output arrangements, e.g. data gloves
• CPC Class Codes: G06F 3/016 Input arrangements with force or tactile feedback as computer generated output to the user
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06F 3/16 Sound input; Sound output speech processing G10L
• CPC Class Codes: G06F 3/167 : Audio in a user interface, e.g. using voice commands for navigating, audio feedback
• CPC Class Codes: G06Q 30/02 : Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06T 11/60 : Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 13/40 : of characters, e.g. humans, animals or virtual beings
• CPC Class Codes: G06T 13/80 : 2D [Two Dimensional] animation, e.g. using sprites
• CPC Class Codes: G06T 15/10 : Geometric effects
• CPC Class Codes: G06T 19/003 : Navigation within 3D models or images
• CPC Class Codes: G06T 19/006 : Mixed reality object pose determination, tracking or camera calibration for mixed reality G06T7/00
• CPC Class Codes: G06T 2200/04 : involving 3D image data
• CPC Class Codes: G06T 2213/08 : Animation software package
• CPC Class Codes: G06T 2215/16 : Using real world measurements to influence rendering
• CPC Class Codes: G06T 2219/024 : Multi-user, collaborative environment
• CPC Class Codes: G06T 7/60 : Analysis of geometric attributes
• CPC Class Codes: G06T 7/70 : Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06V 20/10 : Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• CPC Class Codes: G06V 20/20 : in augmented reality scenes
• CPC Class Codes: G06V 20/653 : by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces
• CPC Class Codes: G06V 20/80 : Recognising image objects characterised by unique random patterns
• CPC Class Codes: H04S 2400/11 : Positioning of individual sound objects, e.g. moving airplane, within a sound field H04S2420/13 takes precedence
• CPC Class Codes: H04S 2400/15 : Aspects of sound capture and related signal processing for recording or reproduction
• CPC Class Codes: H04S 7/304 : For headphones

Abstract

An augmented reality display system comprises a passable world model data comprises a set of map points corresponding to one or more objects of the real world. The augmented reality system also comprises a processor to communicate with one or more individual augmented reality display systems to pass a portion of the passable world model data to the one or more individual augmented reality display systems, wherein the piece of the passable world model data is passed based at least in part on respective locations corresponding to the one or more individual augmented reality display systems.

Claims

1. A method of displaying augmented reality, comprising:

capturing a set of map points from the real world through a plurality of augmented reality systems; and

constructing a geometric map of the real world based at least in part on the captured set of map points, wherein a node of a geometric map comprises a keyframe that captured at least a first set of map points, and a strength of a connection between two nodes of the geometric map corresponds to a number of shared map points between the two nodes.

2. The method of claim 1, further comprising identifying a point of stress in the constructed geometric map.

3. The method of claim 2, wherein the point of stress is identified based at least in part on information retrieved from a topological map.

4. The method of claim 2, wherein the point of stress is identified based at least in part on a discrepancy in a location of a particular keyframe in relation to the geometric map.

5. The method of claim 2, wherein the point of stress is identified based on a maximum residual error of the geometric map.

6. The method of claim 2, wherein the point of stress is distributed through a bundle adjust process.

7. The method of claim 2, wherein the identified point of stress is radially distributed to a first wave of nodes outside the node closest to the identified point of stress.

8. The method of claim 7, wherein the first wave of nodes outside of the node comprises a network or nodes that have a single degree of separation from the node closest to the identified point of stress.

9. The method of claim 7, wherein the identified point of stress is further radially distributed to second wave of nodes outside the first wave of nodes.

10. The method of claim 7, wherein the nodes of the first wave of nodes are marked if the stress is radially distributed to the first wave of nodes.