公开(公告)号：US12238412B2

公开(公告)日：2025-02-25

申请号：US17871262

申请日：2022-07-22

Applicant: Sony Group Corporation ,  Sony Corporation of America

Inventor： Cheng-Yi Liu

IPC: H04N23/60 ,  G06T7/70 ,  G06T17/20

Abstract: An apparatus includes one or more processors and logic encoded in one or more non-transitory media for execution by the one or more processors and when executed operable to receive sensor data from a drone that travels around a target object. The logic is further operable to generate, based on the sensor data, a first three-dimensional (3D) reconstruction of the target object. The logic is further operable to estimate a direction of sunlight and a direction of spectral reflection. The logic is further operable to plan a trajectory of sensor capturing positions for the drone to capture images of the target object that reduce an amount of sunlight and an amount of specular reflection.

公开(公告)号：US12238272B2

公开(公告)日：2025-02-25

申请号：US17739484

申请日：2022-05-09

Applicant: SONY GROUP CORPORATION ,  Sony Corporation of America

Inventor： Alexandre Zaghetto ,  Ali Tabatabai ,  Danillo Graziosi

IPC: H04N19/103 ,  H04N19/119 ,  H04N19/147 ,  H04N19/176 ,  H04N19/42 ,  H04N19/597

Abstract: An electronic device and method for adaptive mode selection for point cloud compression, is provided. The electronic device receives a 3D point cloud geometry and partitions the 3D point cloud geometry into a set of 3D blocks. For a 3D block of the set of 3D blocks, mode decision information is determined. The mode decision information includes class information of the 3D point cloud geometry, operational conditions associated with an encoding stage of the 3D point cloud geometry, or mode-related information associated with one or more 3D blocks of the set of 3D blocks. Based on the mode decision information, one or more modes are selected for the 3D block from a plurality of modes. Each mode corresponds to a function that is used to encode the 3D block. The 3D block is encoded based on the one or more modes.

公开(公告)号：US12231790B2

公开(公告)日：2025-02-18

申请号：US17842077

申请日：2022-06-16

Applicant: Sony Group Corporation ,  Sony Corporation of America

Inventor： Owen Mayer ,  Shohei Noguchi ,  Jiro Takatori ,  Alexander Berestov

IPC: H04N25/702 ,  G06T7/00 ,  H04N17/00

Abstract: A method for optimization of alignment of pixels of X different types on a sensor array for the performance of N different camera tasks, where X and N are integers greater than 1, includes obtaining an output of each of the X types of pixel on the sensor array for an input image; evaluating the quality of the output for each of the N different camera tasks; and obtaining an optimal pixel alignment pattern by adjustment of a potential pixel alignment pattern with respect to performance of the N different camera tasks subject to a user-determined balance of priorities among the N different camera tasks.

公开(公告)号：US12134031B2

公开(公告)日：2024-11-05

申请号：US17488245

申请日：2021-09-28

Applicant: Sony Group Corporation ,  Sony Corporation of America

Inventor： Robert M. McCain ,  Tsubasa Tsukahara

IPC: A63F13/25 ,  G06F3/04815 ,  G06T19/00

Abstract: A method for predefining an entryway, corresponding to a real entryway, for an object entering or leaving an extended reality (XR) space contained within a real environment includes: accessing a spatial mapping mesh (SMM) for the real environment, and a sealed space mesh (SSM) for the XR space; analyzing polygons in the SMM and SSM to identify first subsets representing real boundary walls and virtual wall boundaries respectively; filtering the first subsets according to first criteria to yield second subsets; colliding polygons across the second subsets to yield a third subset of SSM polygons; defining groups of connected SSM polygons within the third subset based on proximity; and selecting one group as defining the entryway. The entryway is predefined in advance of user interaction with any virtual elements in the XR space.

公开(公告)号：US20240357163A1

公开(公告)日：2024-10-24

申请号：US18374848

申请日：2023-09-29

Applicant: SONY GROUP CORPORATION ,  Sony Corporation of America

Inventor： Alexandre Zaghetto ,  Danillo Graziosi ,  Ali Tabatabai

IPC: H04N19/597 ,  H04N19/159 ,  H04N19/172 ,  H04N19/186

CPC classification number: H04N19/597 ,  H04N19/159 ,  H04N19/172 ,  H04N19/186

Abstract: An attribute prediction and compensation scheme for geometry-based dynamic point cloud compression is described herein. A combination of multiple reference frames are able to be used as a predictor for current frames. The method described herein improves efficiency and accuracy.

公开(公告)号：US12083429B2

公开(公告)日：2024-09-10

申请号：US17650300

申请日：2022-02-08

Applicant: Sony Group Corporation ,  Sony Corporation of America

Inventor： Peter Wurman ,  Kaushik Subramanian ,  Florian Fuchs ,  Takuma Seno ,  Kenta Kawamoto

IPC: A63F13/5375 ,  A63F13/49 ,  A63F13/573 ,  A63F13/58 ,  A63F13/803 ,  G06N3/02

CPC classification number: A63F13/5375 ,  A63F13/49 ,  A63F13/573 ,  A63F13/58 ,  A63F13/803 ,  G06N3/02 ,  A63F2300/8017

Abstract: Dynamic driving aides, such as driving lines, turn indicators, braking indicators and acceleration indicators, for example, can be provided for players participating in a racing game. Typically, driving lines are provided for each class of cars. However, even within a class of cars, each car differs enough that the ideal driving lines and breaking points can vary. Therefore, with an agent trained via reinforcement learning, an ideal lines and other driving aides can be established for every individual car. These guides can even be varied to account for variations in the weather or other track conditions.

公开(公告)号：US12078597B2

公开(公告)日：2024-09-03

申请号：US17222131

申请日：2021-04-05

Applicant: SONY GROUP CORPORATION ,  Sony Corporation of America

Inventor： Ming-Chang Liu ,  Su-Hui Chiang

IPC: G01N21/64 ,  G06F18/214 ,  G06F18/231 ,  G06N3/04 ,  G06T7/00 ,  G06V10/44

CPC classification number: G01N21/6486 ,  G01N21/6458 ,  G06F18/214 ,  G06F18/231 ,  G06N3/04 ,  G06T7/0012 ,  G06V10/44 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024

Abstract: A framework that includes a feature extractor and a cluster component for clustering is described herein. The framework supports (1) offline image-based unsupervised clustering that replaces time-consuming manual gating; (2) online image-based single cell sorting. During training, one or multiple cell image datasets with or without ground truth are used to train feature extractor, which is based on a neural network including several convolutional layers. Once trained, the feature extractor is used to extract features of cell images for unsupervised cell clustering and sorting. In addition, additional datasets may be used to further refine the feature extractor after it has been trained.

公开(公告)号：US12039720B2

公开(公告)日：2024-07-16

申请号：US17348436

申请日：2021-06-15

Applicant: Sony Group Corporation ,  Sony Corporation of America

Inventor： Bi Song ,  Ko-Kai Albert Huang ,  Ming-Chang Liu

IPC: G06T7/00 ,  G06N3/045 ,  G06N3/08 ,  G16H10/40 ,  G16H30/40 ,  G16H50/20 ,  G16H70/60

CPC classification number: G06T7/0012 ,  G06N3/045 ,  G06N3/08 ,  G16H10/40 ,  G16H30/40 ,  G16H50/20 ,  G16H70/60 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024 ,  G06T2207/30096

Abstract: A method for automatically estimating cellularity in a digital pathology slide image includes: extracting patches of interest from the digital pathology slide image; operating on each patch using a trained first deep convolutional neural network (DCNN) to classify that patch as either normal, having an estimated cellularity of 0%, or suspect, having a cellularity roughly estimated to be greater than 0%; operating on each suspect patch using a second DCNN, trained using a deep ordinal regression model, to determine an estimated cellularity score for that suspect patch; and combining the estimated cellularity scores of the patches of interest to provide an estimated cellularity for the digital pathology slide image at a patch-by-patch level.

公开(公告)号：US12033281B2

公开(公告)日：2024-07-09

申请号：US17706996

申请日：2022-03-29

Applicant: SONY GROUP CORPORATION ,  Sony Corporation of America

Inventor： Suren Deepak Rajasekaran ,  Hiroyuki Takeda ,  Kenji Tashiro

IPC: G06T17/20 ,  G06T7/20 ,  G06T7/30 ,  G06V40/10

CPC classification number: G06T17/20 ,  G06T7/20 ,  G06T7/30 ,  G06V40/10 ,  G06T2200/04

Abstract: An integrated photo-video volumetric capture system for 3D/4D scanning acquires 3D scans and 4D scans by acquiring images and videos simultaneously. The volumetric capture system for high-quality 4D scanning and mesh-tracking is used to establish topology correspondences across a 4D scanned mesh sequence for generating corrective shapes which will be used in shape interpolation and skeleton driven deformation. The volumetric capture system aids mesh-tracking for maintaining mesh registration (topology consistency) along with ease of extreme pose modeling. Major upper body and lower body joints are able to be identified that are important for generating deformation and capturing the same using a wide range of motion for all movement types across all joint categories. By using the volumetric capture system and mesh tracking, the topology changes are tracked. Each pose captured will have the same topology which makes blending between multiple poses easier and more accurate.

公开(公告)号：US20240221228A1

公开(公告)日：2024-07-04

申请号：US18147944

申请日：2022-12-29

Applicant: SONY GROUP CORPORATION ,  SONY CORPORATION OF AMERICA

Inventor： ALEXANDRE ZAGHETTO ,  DANILLO GRAZIOSI ,  ALI TABATABAI

IPC: G06T9/00 ,  G06T7/62

CPC classification number: G06T9/001 ,  G06T7/62

Abstract: An electronic device and method for detection and indication of geometry reconstruction artifacts is provided. The electronic device acquires a reference point cloud, encodes the reference point cloud to generate encoded point cloud data, and decodes the encoded point cloud data to generate a test point cloud. The electronic device further generates a first local density map and a second local density map for points of the reference point cloud and the test point cloud, respectively. The electronic device generates a final density map based on the first local density map and the second local density map, and further generates supplementary information based on the final density map. The supplementary information includes missing points data corresponding to regions of the test point cloud that include artifacts such as holes or includes descriptors for the regions that include the artifacts. The electronic device signals the supplementary information to a decoder.