Invention Grant
- Patent Title: Training and testing of a neural network method for deep odometry assisted by static scene optical flow
-
Application No.: US15703896Application Date: 2017-09-13
-
Publication No.: US10268205B2Publication Date: 2019-04-23
- Inventor: Wentao Zhu , Yi Wang , Yi Luo
- Applicant: TUSIMPLE
- Applicant Address: US CA San Diego
- Assignee: TUSIMPLE
- Current Assignee: TUSIMPLE
- Current Assignee Address: US CA San Diego
- Agency: WPAT, P.C., Intellectual Property Attorneys
- Agent Anthony King
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G05D1/02 ; G06N3/08 ; G06T7/207 ; G06K9/32 ; G06T7/246

Abstract:
A method of visual odometry for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs include instructions, which when executed by a computing device, causes the computing device to perform the following steps comprising: in response to images in pairs, generating a prediction of static scene optical flow for each pair of the images in a visual odometry model; generating a set of motion parameters for each pair of the images in the visual odometry model; training the visual odometry model by using the prediction of static scene optical flow and the motion parameters; and predicting motion between a pair of consecutive image frames by the trained visual odometry model.
Public/Granted literature
- US20190079535A1 TRAINING AND TESTING OF A NEURAL NETWORK METHOD FOR DEEP ODOMETRY ASSISTED BY STATIC SCENE OPTICAL FLOW Public/Granted day:2019-03-14
Information query