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    OBJECT SEGMENTATION AND FEATURE TRACKING
    2.
    发明公开
    OBJECT SEGMENTATION AND FEATURE TRACKING 审中-公开

    公开(公告)号：US20230342943A1

    公开(公告)日：2023-10-26

    申请号：US18343591

    申请日：2023-06-28

    Applicant: QUALCOMM Incorporated

    Inventor： Abhijeet BISAIN ,  Gerhard REITMAYR

    IPC: G06T7/174

    CPC classification number: G06T7/174 ,  G06T2207/20084

    Abstract: Examples are described for processing images to mask dynamic objects out of images to improve feature tracking between images. A device receives an image of an environment captured by an image sensor. The image depicts at least a static portion of the environment and a dynamic object in the environment. The device identifies a portion of the image that includes a depiction of the dynamic object. For example, the device can detect a bounding box around the dynamic object, or can detect which pixels in the image correspond to the dynamic object. The device generates a masked image at least by masking the portion of the image. The device identifies features in the masked image, and uses the features from the masked image for feature tracking from other images of the environment, masked or otherwise. The device can use this feature tracking for mapping, localization, and/or relocation.

    AUTO-CALIBRATING LIGHT SENSOR DATA OF A MOBILE DEVICE
    4.
    发明申请
    AUTO-CALIBRATING LIGHT SENSOR DATA OF A MOBILE DEVICE 审中-公开
    自动校准光传感器数据的移动设备

    公开(公告)号：US20170059401A1

    公开(公告)日：2017-03-02

    申请号：US14843790

    申请日：2015-09-02

    Applicant: QUALCOMM Incorporated

    Inventor： Santiago MAZUELAS ,  Ashwin SWAMINATHAN ,  Piero ZAPPI ,  Muralidhar Reddy AKULA ,  Abhijeet BISAIN ,  Aditya Narain SRIVASTAVA ,  Suhas Hariharapura SHESHADRI

    IPC: G01J1/44 ,  G01J1/42

    CPC classification number: G01J1/44 ,  G01J1/4204 ,  G01J2001/444 ,  G06F9/4405 ,  H04M1/22 ,  H04M1/72569 ,  H04M2250/12

    Abstract: A method of auto-calibrating light sensor data of a mobile device includes, obtaining, by the mobile device, one or more reference parameters representative of light sensor data collected by a reference device. The method also includes collecting, by the mobile device, light sensor data from a light sensor included in the mobile device, itself. One or more sample parameters of the light sensor data obtained from the light sensor included in the mobile device are then calculated. A calibration model is then determined for auto-calibrating the light sensor data of the light sensor included in the mobile device based on the one or more reference parameters and the one or more sample parameters.

    Abstract translation: 自动校准移动设备的光传感器数据的方法包括：由移动设备获得表示由参考设备收集的光传感器数据的一个或多个参考参数。 该方法还包括由移动设备从包括在移动设备中的光传感器本身收集光传感器数据。 然后计算从包括在移动设备中的光传感器获得的光传感器数据的一个或多个采样参数。 然后，基于一个或多个参考参数和一个或多个样本参数，确定校准模型，用于自动校准包括在移动设备中的光传感器的光传感器数据。

    GEOMETRY-AWARE SEMANTICS SEGMENTATION WITH GRAVITY-NORMAL REGULARIZATION
    5.
    发明申请
    GEOMETRY-AWARE SEMANTICS SEGMENTATION WITH GRAVITY-NORMAL REGULARIZATION 有权

    公开(公告)号：US20250086995A1

    公开(公告)日：2025-03-13

    申请号：US18463068

    申请日：2023-09-07

    Applicant: QUALCOMM Incorporated

    Inventor： Ching-Wei TSENG ,  Mohsen GHAFOORIAN ,  Nikhil KHULLAR ,  Yu FU ,  Shang-Lun LEE ,  Abhijeet BISAIN

    IPC: G06V20/70 ,  G06T7/11

    Abstract: Disclosed are systems and techniques for image processing. For example, a computing device can generate, using a multi-task model, a segmentation output and a normal output based on image(s) of a scene and a gravity vector for the scene. The computing device can learn semantic prediction(s) based on comparing the segmentation output to at least one ground truth semantic segmentation map. The computing device can also learn normal prediction(s) based on comparing the normal output to at least one ground truth normal map. The computing device can extract a semantics normal from the semantic prediction(s) and the normal prediction(s). The computing device can optimize a regularization loss based on the semantics normal and the gravity vector for the scene by learning gravity-normal regularization(s) for the scene. The computing device can determine final semantic labels for regions of the scene based on the gravity-normal regularization(s).

    SYSTEMS AND METHODS FOR MANAGEMENT OF NON-FUNGIBLE TOKENS AND CORRESPONDING DIGITAL ASSETS
    8.
    发明申请
    SYSTEMS AND METHODS FOR MANAGEMENT OF NON-FUNGIBLE TOKENS AND CORRESPONDING DIGITAL ASSETS 有权

    公开(公告)号：US20230004627A1

    公开(公告)日：2023-01-05

    申请号：US17832397

    申请日：2022-06-03

    Applicant: QUALCOMM Incorporated

    Inventor： Wesley James HOLLAND ,  Jonathan KIES ,  Brian VOGELSANG ,  Abhijeet BISAIN ,  William WHYTE ,  Michael Franco TAVEIRA

    IPC: G06F21/10 ,  G06F21/44

    Abstract: Systems and techniques are described for token device transfer management. A system identifies, in a payload of at least one block of a distributed ledger, a token corresponding to media content. A parameter of the token in the distributed ledger indicates that the token is associated with a first user. The system identifies a device that is associated with the token and the media content. The device is also associated with the first user. The system identifies that the device has been relocated to an area associated with a second user. In response to identifying that the device has been relocated to the area, the system causes the parameter of the token in the distributed ledger to be modified from indicating that the token is associated with the first user to indicating that the token is associated with the second user.

    FEATURE PROCESSING IN EXTENDED REALITY SYSTEMS
    10.
    发明申请
    FEATURE PROCESSING IN EXTENDED REALITY SYSTEMS 有权

    公开(公告)号：US20220245832A1

    公开(公告)日：2022-08-04

    申请号：US17166957

    申请日：2021-02-03

    Applicant: QUALCOMM Incorporated

    Inventor： Ajit Deepak GUPTE ,  Gerhard REITMAYR ,  Abhijeet BISAIN ,  Pushkar GORUR SHESHAGIRI ,  Chayan SHARMA ,  Ajit Venkat RAO

    IPC: G06T7/246 ,  G06T7/73 ,  G06T7/292

    Abstract: Systems and techniques are described herein for processing images. The systems and techniques can be implemented by various types of systems, such as by an extended reality (XR) system or device. In some cases, a first processor receives an image of an environment captured by an image sensor, identifies features depicted in the image, and generates descriptors for the features. The first processor sends the descriptors to a second processor, which may be more powerful than the first processor. The second processor receives the descriptors. The second processor associates the plurality of features with a map of the environment based on at least a subset of the plurality of descriptors. For example, the second processor can track at least a subset of the features based on at least a subset of the descriptors and based on feature information from one or more additional images of the environment.

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