Open Access System for Information Sharing

Login Library

 

Conference
Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Imaging-sonar-based Object Recognition Utilizing Object's Yaw Angle Estimation with Deep Learning Technique

Title
Imaging-sonar-based Object Recognition Utilizing Object's Yaw Angle Estimation with Deep Learning Technique
Authors
YU, SON CHEOLMinsung SungMEUNGSUK, LEEBYEONGJIN, KIM
Date Issued
11-Jul-2020
Publisher
IFAC(International Federation of Automatic Control)
Abstract
This paper proposes a method to recognize underwater target objects and estimate their yaw angle using an imaging sonar. First, a fast sonar simulator generated template images of the target objects for various viewpoints. Next, a generative adversarial network (GAN) generated a semantic map by segmenting the real sonar image for reliable recognition. Then, matching the template image and the semantic map identies the target object and yaw angle of the object. We veried the proposed method through indoor water tank experiments by installing objects and acquiring images from various angles. The proposed method can provide relative position and bearing information of a sensing platform so that it can be applied to various algorithms such as pose control and navigation.
URI
http://oasis.postech.ac.kr/handle/2014.oak/104060
Article Type
Conference
Citation
2020 IFAC World Congress, page. 1 - 6, 2020-07-11
Files in This Item:
There are no files associated with this item.

qr_code

  • mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher

유선철YU, SON CHEOL
Div. of Advanced Nuclear Enginrg
Read more

Views & Downloads

Browse