Depth-map driven planar surfaces detection

Zhi Jin; Tammam Tillo; Fei Cheng

doi:10.1109/VCIP.2014.7051619

Depth-map driven planar surfaces detection

Zhi Jin, Tammam Tillo, Fei Cheng

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

9 Citations (Scopus)

Abstract

Planar surface is a common feature in man-made structure, thus accurate detection of planar surface can benefit the image/video segmentation and reconstruction and also the navigation system of robots. Since depth map represents the distance from one object to the capturing camera in a grey image, it also can represent the surface characteristics of the objects. So in this paper, we propose a novel Depth-map Driven Planar Surface Detection (DDPSD) method, where detection starts from 'the most flat' seed patch on the depth map and uses dynamic threshold value and surface function to control the growing process. Compared with one of the popular planar surface detection algorithms, RANdom SAmples Consensus (RANSAC), the accuracy of the proposed method is obviously superior on typical indoor scenes. Moreover, semi-planar surfaces can be also successfully detected by the proposed method.

Original language	English
Title of host publication	2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	514-517
Number of pages	4
ISBN (Electronic)	9781479961399
DOIs	https://doi.org/10.1109/VCIP.2014.7051619
Publication status	Published - 27 Feb 2015
Event	2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014 - Valletta, Malta Duration: 7 Dec 2014 → 10 Dec 2014

Publication series

Name	2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014

Conference

Conference	2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014
Country/Territory	Malta
City	Valletta
Period	7/12/14 → 10/12/14

Keywords

Depth Map
Dynamic Control
Planar Surfaces Detection
Seed Growing

Access to Document

10.1109/VCIP.2014.7051619

Cite this

@inproceedings{99fddb54bbe04d6fb4265e93afcdae9d,

title = "Depth-map driven planar surfaces detection",

abstract = "Planar surface is a common feature in man-made structure, thus accurate detection of planar surface can benefit the image/video segmentation and reconstruction and also the navigation system of robots. Since depth map represents the distance from one object to the capturing camera in a grey image, it also can represent the surface characteristics of the objects. So in this paper, we propose a novel Depth-map Driven Planar Surface Detection (DDPSD) method, where detection starts from 'the most flat' seed patch on the depth map and uses dynamic threshold value and surface function to control the growing process. Compared with one of the popular planar surface detection algorithms, RANdom SAmples Consensus (RANSAC), the accuracy of the proposed method is obviously superior on typical indoor scenes. Moreover, semi-planar surfaces can be also successfully detected by the proposed method.",

keywords = "Depth Map, Dynamic Control, Planar Surfaces Detection, Seed Growing",

author = "Zhi Jin and Tammam Tillo and Fei Cheng",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.. {\textcopyright} 2014 IEEE.; 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014 ; Conference date: 07-12-2014 Through 10-12-2014",

year = "2015",

month = feb,

day = "27",

doi = "10.1109/VCIP.2014.7051619",

language = "English",

series = "2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014",

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

pages = "514--517",

booktitle = "2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014",

}

Jin, Z, Tillo, T & Cheng, F 2015, Depth-map driven planar surfaces detection. in 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014., 7051619, 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014, Institute of Electrical and Electronics Engineers Inc., pp. 514-517, 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014, Valletta, Malta, 7/12/14. https://doi.org/10.1109/VCIP.2014.7051619

Depth-map driven planar surfaces detection. / Jin, Zhi; Tillo, Tammam; Cheng, Fei.
2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014. Institute of Electrical and Electronics Engineers Inc., 2015. p. 514-517 7051619 (2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Depth-map driven planar surfaces detection

AU - Jin, Zhi

AU - Tillo, Tammam

AU - Cheng, Fei

PY - 2015/2/27

Y1 - 2015/2/27

N2 - Planar surface is a common feature in man-made structure, thus accurate detection of planar surface can benefit the image/video segmentation and reconstruction and also the navigation system of robots. Since depth map represents the distance from one object to the capturing camera in a grey image, it also can represent the surface characteristics of the objects. So in this paper, we propose a novel Depth-map Driven Planar Surface Detection (DDPSD) method, where detection starts from 'the most flat' seed patch on the depth map and uses dynamic threshold value and surface function to control the growing process. Compared with one of the popular planar surface detection algorithms, RANdom SAmples Consensus (RANSAC), the accuracy of the proposed method is obviously superior on typical indoor scenes. Moreover, semi-planar surfaces can be also successfully detected by the proposed method.

AB - Planar surface is a common feature in man-made structure, thus accurate detection of planar surface can benefit the image/video segmentation and reconstruction and also the navigation system of robots. Since depth map represents the distance from one object to the capturing camera in a grey image, it also can represent the surface characteristics of the objects. So in this paper, we propose a novel Depth-map Driven Planar Surface Detection (DDPSD) method, where detection starts from 'the most flat' seed patch on the depth map and uses dynamic threshold value and surface function to control the growing process. Compared with one of the popular planar surface detection algorithms, RANdom SAmples Consensus (RANSAC), the accuracy of the proposed method is obviously superior on typical indoor scenes. Moreover, semi-planar surfaces can be also successfully detected by the proposed method.

KW - Depth Map

KW - Dynamic Control

KW - Planar Surfaces Detection

KW - Seed Growing

UR - http://www.scopus.com/inward/record.url?scp=84925449935&partnerID=8YFLogxK

U2 - 10.1109/VCIP.2014.7051619

DO - 10.1109/VCIP.2014.7051619

M3 - Conference Proceeding

AN - SCOPUS:84925449935

T3 - 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014

SP - 514

EP - 517

BT - 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014

Y2 - 7 December 2014 through 10 December 2014

ER -

Depth-map driven planar surfaces detection

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Cite this