Object recognition for SLAM in floor environments using a depth sensor

Hee Won Chae; Chansoo Park; Hyejun Yu; Jae-Bok Song

doi:10.1109/URAI.2016.7734070

Object recognition for SLAM in floor environments using a depth sensor

Hee Won Chae, Chansoo Park, Hyejun Yu, Jae-Bok Song

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

8 Citations (Scopus)

Abstract

Depth sensors have been increasingly used for object recognition in recent years. However, it is very challenging for simultaneous localization and mapping (SLAM) to make use of the forward scenes from a depth sensor. To this end, we introduce the object recognition framework for SLAM in indoor environments based on the extraction of an object-level descriptor. The proposed object-level descriptor can be obtained based on the surface appearances acquired from a depth sensor without any training. To express the surface normal distribution, a well-known descriptor, fast point feature histogram (FPFH), with a small sampling radius is used to define basic shape elements of a plane, a cylinder and a sphere. The object-level descriptor to recognize the objects can be obtained using these shape elements. Several experiments on arbitrary objects on the floor show the proposed scheme is useful in object recognition and generation of the feature map.

Original language	English
Title of host publication	2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	405-410
Number of pages	6
ISBN (Electronic)	9781509008216
DOIs	https://doi.org/10.1109/URAI.2016.7734070
Publication status	Published - 2016 Oct 21
Event	13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 - Xian, China Duration: 2016 Aug 19 → 2016 Aug 22

Publication series

Name	2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016

Other

Other	13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016
Country/Territory	China
City	Xian
Period	16/8/19 → 16/8/22

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Depth sensor
Object recognition
SLAM

ASJC Scopus subject areas

Modelling and Simulation
Artificial Intelligence
Control and Optimization

Access to Document

10.1109/URAI.2016.7734070

Cite this

Chae, H. W., Park, C., Yu, H., & Song, J.-B. (2016). Object recognition for SLAM in floor environments using a depth sensor. In 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 (pp. 405-410). Article 7734070 (2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/URAI.2016.7734070

Object recognition for SLAM in floor environments using a depth sensor. / Chae, Hee Won; Park, Chansoo; Yu, Hyejun et al.
2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 405-410 7734070 (2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016).

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

Chae, HW, Park, C, Yu, H & Song, J-B 2016, Object recognition for SLAM in floor environments using a depth sensor. in 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016., 7734070, 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016, Institute of Electrical and Electronics Engineers Inc., pp. 405-410, 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016, Xian, China, 16/8/19. https://doi.org/10.1109/URAI.2016.7734070

Chae HW, Park C, Yu H, Song JB. Object recognition for SLAM in floor environments using a depth sensor. In 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 405-410. 7734070. (2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016). doi: 10.1109/URAI.2016.7734070

Chae, Hee Won ; Park, Chansoo ; Yu, Hyejun et al. / Object recognition for SLAM in floor environments using a depth sensor. 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 405-410 (2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016).

@inproceedings{fe450e5a352e4106a04105feb3230486,

title = "Object recognition for SLAM in floor environments using a depth sensor",

abstract = "Depth sensors have been increasingly used for object recognition in recent years. However, it is very challenging for simultaneous localization and mapping (SLAM) to make use of the forward scenes from a depth sensor. To this end, we introduce the object recognition framework for SLAM in indoor environments based on the extraction of an object-level descriptor. The proposed object-level descriptor can be obtained based on the surface appearances acquired from a depth sensor without any training. To express the surface normal distribution, a well-known descriptor, fast point feature histogram (FPFH), with a small sampling radius is used to define basic shape elements of a plane, a cylinder and a sphere. The object-level descriptor to recognize the objects can be obtained using these shape elements. Several experiments on arbitrary objects on the floor show the proposed scheme is useful in object recognition and generation of the feature map.",

keywords = "Depth sensor, Object recognition, SLAM",

author = "Chae, {Hee Won} and Chansoo Park and Hyejun Yu and Jae-Bok Song",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 ; Conference date: 19-08-2016 Through 22-08-2016",

year = "2016",

month = oct,

day = "21",

doi = "10.1109/URAI.2016.7734070",

language = "English",

series = "2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016",

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

pages = "405--410",

booktitle = "2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016",

}

TY - GEN

T1 - Object recognition for SLAM in floor environments using a depth sensor

AU - Chae, Hee Won

AU - Park, Chansoo

AU - Yu, Hyejun

AU - Song, Jae-Bok

PY - 2016/10/21

Y1 - 2016/10/21

N2 - Depth sensors have been increasingly used for object recognition in recent years. However, it is very challenging for simultaneous localization and mapping (SLAM) to make use of the forward scenes from a depth sensor. To this end, we introduce the object recognition framework for SLAM in indoor environments based on the extraction of an object-level descriptor. The proposed object-level descriptor can be obtained based on the surface appearances acquired from a depth sensor without any training. To express the surface normal distribution, a well-known descriptor, fast point feature histogram (FPFH), with a small sampling radius is used to define basic shape elements of a plane, a cylinder and a sphere. The object-level descriptor to recognize the objects can be obtained using these shape elements. Several experiments on arbitrary objects on the floor show the proposed scheme is useful in object recognition and generation of the feature map.

AB - Depth sensors have been increasingly used for object recognition in recent years. However, it is very challenging for simultaneous localization and mapping (SLAM) to make use of the forward scenes from a depth sensor. To this end, we introduce the object recognition framework for SLAM in indoor environments based on the extraction of an object-level descriptor. The proposed object-level descriptor can be obtained based on the surface appearances acquired from a depth sensor without any training. To express the surface normal distribution, a well-known descriptor, fast point feature histogram (FPFH), with a small sampling radius is used to define basic shape elements of a plane, a cylinder and a sphere. The object-level descriptor to recognize the objects can be obtained using these shape elements. Several experiments on arbitrary objects on the floor show the proposed scheme is useful in object recognition and generation of the feature map.

KW - Depth sensor

KW - Object recognition

KW - SLAM

UR - http://www.scopus.com/inward/record.url?scp=85000443208&partnerID=8YFLogxK

U2 - 10.1109/URAI.2016.7734070

DO - 10.1109/URAI.2016.7734070

M3 - Conference contribution

AN - SCOPUS:85000443208

T3 - 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016

SP - 405

EP - 410

BT - 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016

Y2 - 19 August 2016 through 22 August 2016

ER -

Object recognition for SLAM in floor environments using a depth sensor

Abstract

Publication series

Other

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this