公开(公告)号：US20230298266A1

公开(公告)日：2023-09-21

申请号：US18071295

申请日：2022-11-29

Applicant: Apple Inc.

Inventor： Payal Jotwani ,  Angela Blechschmidt

IPC: G06T17/00 ,  G06V20/70

CPC classification number: G06T17/00 ,  G06V20/70

Abstract: In one implementation, a method of providing a portion of a three-dimensional scene model includes storing, in the non-transitory memory, a three-dimensional scene model of a physical environment including a plurality of points, wherein each of the plurality of points is associated with a set of coordinates in a three-dimensional space, wherein a subset of the plurality of points is associated with a hierarchical data set including a plurality of layers. The method includes receiving, from an objective-effectuator, a request for a portion of the three-dimensional scene model, wherein the portion of the three-dimensional scene model includes less than all of the plurality of points or less than all of the plurality of layers. The method includes obtaining, by the processor from the non-transitory memory, the portion of the three-dimensional scene model. The method includes providing, to the objective-effectuator, the portion of the three-dimensional scene model.

公开(公告)号：US11640708B1

公开(公告)日：2023-05-02

申请号：US17227724

申请日：2021-04-12

Applicant: Apple Inc.

Inventor： Angela Blechschmidt ,  Alexander S. Polichroniadis ,  Daniel Ulbricht

IPC: G06V20/10 ,  G06K9/62 ,  G06V20/40

Abstract: Implementations disclosed herein provide systems and methods that match a current scene graph associated with a user's current environment to a prior scene graph for a prior environment to determine that the user is in the same environment. The current scene graph is compared with the prior scene graph based on matching the objects within the current scene graph with objects within the prior scene graph.

公开(公告)号：US11610397B2

公开(公告)日：2023-03-21

申请号：US17473469

申请日：2021-09-13

Applicant: Apple Inc.

Inventor： Daniel Ulbricht ,  Angela Blechschmidt ,  Mohammad Haris Baig ,  Tanmay Batra ,  Eshan Verma ,  Amit Kumar KC

IPC: G06V20/10 ,  G06T7/70 ,  G06V30/262 ,  G06K9/62 ,  G06T19/00

Abstract: In one implementation, a method of generating a plane hypothesis is performed by a device including one or more processors, non-transitory memory, and a scene camera. The method includes obtaining an image of a scene including a plurality of pixels. The method includes obtaining a plurality of points of a point cloud based on the image of the scene. The method includes obtaining an object classification set based on the image of the scene. Each element of the object classification set includes a plurality of pixels respectively associated with a corresponding object in the scene. The method includes detecting a plane within the scene by identifying a subset of the plurality of points of the point cloud that correspond to a particular element of the object classification set.

公开(公告)号：US11468275B1

公开(公告)日：2022-10-11

申请号：US16744425

申请日：2020-01-16

Applicant: Apple Inc.

Inventor： Angela Blechschmidt ,  Daniel Ulbricht ,  Mohammad Haris Baig

IPC: G06K9/62 ,  G06N20/00 ,  G06V10/20 ,  G06N3/08

Abstract: A machine learning (ML) model is trained and used to produce a probability distribution associated with a computer vision task. The ML model uses a prior probability distribution associated with a particular image capture condition determined based on sensor data. For example, given that an image was captured by an image capture device at a particular height above the floor and angle relative to the vertical world axis, a prior probability distribution for that particular image capture device condition can be used in performing a computer vision task on the image. Accordingly, the machine learning model is given the image as input as well as the prior probability distribution for the particular image capture device condition. The use of the prior probability distribution can improve the accuracy, efficiency, or effectiveness of the ML learning model for the computer vison task.

公开(公告)号：US11430238B1

公开(公告)日：2022-08-30

申请号：US16838934

申请日：2020-04-02

Applicant: Apple Inc.

Inventor： Angela Blechschmidt ,  Mohammad Haris Baig ,  Daniel Ulbricht

IPC: G06V30/262 ,  G06K9/62 ,  G06V10/40 ,  G06N3/04 ,  G06T7/60 ,  G06N3/08

Abstract: In one implementation, a method of generating a confidence value for a result from a primary task is performed at an image processing system. The method includes obtaining, by a feature extractor portion of the neural network, a set of feature maps for an image data frame; generating a contextual information vector associated with the image data frame based on results from one or more auxiliary tasks performed on the set of feature maps by an auxiliary task sub-network portion of the neural network; performing, by a primary task sub-network portion of the neural network, a primary task on the set of feature maps for the image data frame in order to generate a primary task result; and generating a confidence value based on the contextual information vector, wherein the confidence value corresponds to a reliability metric for the primary task result.

公开(公告)号：US10896548B1

公开(公告)日：2021-01-19

申请号：US16580176

申请日：2019-09-24

Applicant: Apple Inc.

Inventor： Daniel Ulbricht ,  Amit Kumar K C ,  Angela Blechschmidt ,  Chen-Yu Lee ,  Eshan Verma ,  Mohammad Haris Baig ,  Tanmay Batra

IPC: G06T19/00 ,  G06F3/01 ,  A63F13/825 ,  G02B27/01 ,  A63F13/212 ,  G06F3/03

Abstract: In one implementation, a method of including a person in a CGR experience or excluding the person from the CGR experience is performed by a device including one or more processors, non-transitory memory, and a scene camera. The method includes, while presenting a CGR experience, capturing an image of scene; detecting, in the image of the scene, a person; and determining an identity of the person. The method includes determining, based on the identity of the person, whether to include the person in the CGR experience or exclude the person from the CGR experience. The method includes presenting the CGR experience based on the determination.