Invention Grant
- Patent Title: User-specific learning for improved pedestrian motion modeling in a mobile device
-
Application No.: US15275014Application Date: 2016-09-23
-
Publication No.: US10323942B2Publication Date: 2019-06-18
- Inventor: Benjamin Werner , William Morrison , Ning Luo , Ming Sun , Joseph Czompo
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Agent Thien T. Nguyen
- Main IPC: H04W4/38
- IPC: H04W4/38 ; G01C21/14 ; G01C21/16 ; G01C22/00 ; G01S19/26 ; G01S19/49 ; H04W4/029 ; H04W4/33

Abstract:
Techniques provided herein are directed toward enabling on-device learning to create user-specific movement models that can be used for dead reckoning. Because these moving models are user-specific, they can be later used to identify user-specific motions in a manner that provides for a dead reckoning location estimation. In some embodiments, these models can be focused on pedestrian movement, based on the repetitive motion that occurs when a user takes a stride (walking, jogging, running, etc.) or other repetitive motion (swimming, riding a horse, etc.).
Public/Granted literature
- US20180087903A1 USER-SPECIFIC LEARNING FOR IMPROVED PEDESTRIAN MOTION MODELING IN A MOBILE DEVICE Public/Granted day:2018-03-29
Information query