- Patent Title: Human pose estimation using neural networks and kinematic structure
-
Application No.: US15929811Application Date: 2020-05-22
-
Publication No.: US11335023B2Publication Date: 2022-05-17
- Inventor: Sameh Khamis , Christian Haene , Hossam Isack , Cem Keskin , Sofien Bouaziz , Shahram Izadi
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Brake Hughes Bellermann LLP
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06T7/73 ; G06T3/40 ; G06T11/00 ; G06N3/08 ; G06N3/04

Abstract:
According to an aspect, a method for pose estimation using a convolutional neural network includes extracting features from an image, downsampling the features to a lower resolution, arranging the features into sets of features, where each set of features corresponds to a separate keypoint of a pose of a subject, updating, by at least one convolutional block, each set of features based on features of one or more neighboring keypoints using a kinematic structure, and predicting the pose of the subject using the updated sets of features.
Public/Granted literature
- US20210366146A1 HUMAN POSE ESTIMATION USING NEURAL NETWORKS AND KINEMATIC STRUCTURE Public/Granted day:2021-11-25
Information query