Multi-resolution point cloud generation based on heterogeneous sensor fusion system

Hyung Gi Jo; Hae Min Cho; Seongwon Lee; Euntai Kim

doi:10.1109/URAI.2017.7992856

Multi-resolution point cloud generation based on heterogeneous sensor fusion system

Hyung Gi Jo, Hae Min Cho, Seongwon Lee, Euntai Kim

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Various three-dimensional environment representation techniques exist depending on the type of sensor, and the level of expression varies depending on the characteristics of the sensor. Our sensor system is composed of a three-dimensional lasers scanner and a stereo camera. A rigid transformation matrix representing a three-dimensional relative pose is obtained by calibration between a stereo camera and laser scanner and creates a multi-resolution point cloud. By combining a stereo camera with a high resolution and a laser scanner with wide range and low-resolution, it is able to complement each other and achieve better results.

Original language	English
Title of host publication	2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	886-888
Number of pages	3
ISBN (Electronic)	9781509030552
DOIs	https://doi.org/10.1109/URAI.2017.7992856
Publication status	Published - 2017 Jul 25
Event	14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017 - Jeju, Korea, Republic of Duration: 2017 Jun 28 → 2017 Jul 1

Publication series

Name	2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017

Other

Other	14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017
Country	Korea, Republic of
City	Jeju
Period	17/6/28 → 17/7/1

All Science Journal Classification (ASJC) codes

Computer Science Applications
Biomedical Engineering
Artificial Intelligence
Human-Computer Interaction
Control and Optimization

Access to Document

10.1109/URAI.2017.7992856

Fingerprint Dive into the research topics of 'Multi-resolution point cloud generation based on heterogeneous sensor fusion system'. Together they form a unique fingerprint.

Cite this

Jo, H. G., Cho, H. M., Lee, S., & Kim, E. (2017). Multi-resolution point cloud generation based on heterogeneous sensor fusion system. In 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017 (pp. 886-888). [7992856] (2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/URAI.2017.7992856

Jo, Hyung Gi ; Cho, Hae Min ; Lee, Seongwon ; Kim, Euntai. / Multi-resolution point cloud generation based on heterogeneous sensor fusion system. 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 886-888 (2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017).

@inproceedings{02342f87852f4c93b8b0417c839721ba,

title = "Multi-resolution point cloud generation based on heterogeneous sensor fusion system",

abstract = "Various three-dimensional environment representation techniques exist depending on the type of sensor, and the level of expression varies depending on the characteristics of the sensor. Our sensor system is composed of a three-dimensional lasers scanner and a stereo camera. A rigid transformation matrix representing a three-dimensional relative pose is obtained by calibration between a stereo camera and laser scanner and creates a multi-resolution point cloud. By combining a stereo camera with a high resolution and a laser scanner with wide range and low-resolution, it is able to complement each other and achieve better results.",

author = "Jo, {Hyung Gi} and Cho, {Hae Min} and Seongwon Lee and Euntai Kim",

year = "2017",

month = jul,

day = "25",

doi = "10.1109/URAI.2017.7992856",

language = "English",

series = "2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "886--888",

booktitle = "2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017",

address = "United States",

note = "14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017 ; Conference date: 28-06-2017 Through 01-07-2017",

}

Jo, HG, Cho, HM, Lee, S & Kim, E 2017, Multi-resolution point cloud generation based on heterogeneous sensor fusion system. in 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017., 7992856, 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017, Institute of Electrical and Electronics Engineers Inc., pp. 886-888, 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017, Jeju, Korea, Republic of, 17/6/28. https://doi.org/10.1109/URAI.2017.7992856

Multi-resolution point cloud generation based on heterogeneous sensor fusion system. / Jo, Hyung Gi; Cho, Hae Min; Lee, Seongwon; Kim, Euntai.

2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 886-888 7992856 (2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Multi-resolution point cloud generation based on heterogeneous sensor fusion system

AU - Jo, Hyung Gi

AU - Cho, Hae Min

AU - Lee, Seongwon

AU - Kim, Euntai

PY - 2017/7/25

Y1 - 2017/7/25

N2 - Various three-dimensional environment representation techniques exist depending on the type of sensor, and the level of expression varies depending on the characteristics of the sensor. Our sensor system is composed of a three-dimensional lasers scanner and a stereo camera. A rigid transformation matrix representing a three-dimensional relative pose is obtained by calibration between a stereo camera and laser scanner and creates a multi-resolution point cloud. By combining a stereo camera with a high resolution and a laser scanner with wide range and low-resolution, it is able to complement each other and achieve better results.

AB - Various three-dimensional environment representation techniques exist depending on the type of sensor, and the level of expression varies depending on the characteristics of the sensor. Our sensor system is composed of a three-dimensional lasers scanner and a stereo camera. A rigid transformation matrix representing a three-dimensional relative pose is obtained by calibration between a stereo camera and laser scanner and creates a multi-resolution point cloud. By combining a stereo camera with a high resolution and a laser scanner with wide range and low-resolution, it is able to complement each other and achieve better results.

UR - http://www.scopus.com/inward/record.url?scp=85034251054&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85034251054&partnerID=8YFLogxK

U2 - 10.1109/URAI.2017.7992856

DO - 10.1109/URAI.2017.7992856

M3 - Conference contribution

AN - SCOPUS:85034251054

T3 - 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017

SP - 886

EP - 888

BT - 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017

Y2 - 28 June 2017 through 1 July 2017

ER -

Jo HG, Cho HM, Lee S, Kim E. Multi-resolution point cloud generation based on heterogeneous sensor fusion system. In 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 886-888. 7992856. (2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017). https://doi.org/10.1109/URAI.2017.7992856