Glass object localization by joint inference of boundary and depth

Tao Wang; Xuming He; Nick Barnes

Glass object localization by joint inference of boundary and depth

Tao Wang^*, Xuming He, Nick Barnes

^*Corresponding author for this work

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

28 Citations (Scopus)

Abstract

We address the problem of localizing glass objects with a multimodal RGB-D camera. Our method integrates the intensity and depth information from a single view point, and builds a Markov Random Field that predicts glass boundary and region jointly. Based on the localization, we also reconstruct the depth of the scene and fill in the missing depth values. The efficacy of our algorithm is validated on a new RGB-D Glass dataset of 43 distinct glass objects.

Original language	English
Title of host publication	ICPR 2012 - 21st International Conference on Pattern Recognition
Pages	3783-3786
Number of pages	4
Publication status	Published - 2012
Event	21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan Duration: 11 Nov 2012 → 15 Nov 2012

Publication series

Name	Proceedings - International Conference on Pattern Recognition
ISSN (Print)	1051-4651

Conference

Conference	21st International Conference on Pattern Recognition, ICPR 2012
Country/Territory	Japan
City	Tsukuba
Period	11/11/12 → 15/11/12

Cite this

@inproceedings{b9758e98aa824dad8890883950d430b6,

title = "Glass object localization by joint inference of boundary and depth",

abstract = "We address the problem of localizing glass objects with a multimodal RGB-D camera. Our method integrates the intensity and depth information from a single view point, and builds a Markov Random Field that predicts glass boundary and region jointly. Based on the localization, we also reconstruct the depth of the scene and fill in the missing depth values. The efficacy of our algorithm is validated on a new RGB-D Glass dataset of 43 distinct glass objects.",

author = "Tao Wang and Xuming He and Nick Barnes",

year = "2012",

language = "English",

isbn = "9784990644109",

series = "Proceedings - International Conference on Pattern Recognition",

pages = "3783--3786",

booktitle = "ICPR 2012 - 21st International Conference on Pattern Recognition",

note = "21st International Conference on Pattern Recognition, ICPR 2012 ; Conference date: 11-11-2012 Through 15-11-2012",

}

TY - GEN

T1 - Glass object localization by joint inference of boundary and depth

AU - Wang, Tao

AU - He, Xuming

AU - Barnes, Nick

PY - 2012

Y1 - 2012

N2 - We address the problem of localizing glass objects with a multimodal RGB-D camera. Our method integrates the intensity and depth information from a single view point, and builds a Markov Random Field that predicts glass boundary and region jointly. Based on the localization, we also reconstruct the depth of the scene and fill in the missing depth values. The efficacy of our algorithm is validated on a new RGB-D Glass dataset of 43 distinct glass objects.

AB - We address the problem of localizing glass objects with a multimodal RGB-D camera. Our method integrates the intensity and depth information from a single view point, and builds a Markov Random Field that predicts glass boundary and region jointly. Based on the localization, we also reconstruct the depth of the scene and fill in the missing depth values. The efficacy of our algorithm is validated on a new RGB-D Glass dataset of 43 distinct glass objects.

UR - https://www.scopus.com/pages/publications/84874572202

M3 - Conference Paper

SN - 9784990644109

T3 - Proceedings - International Conference on Pattern Recognition

SP - 3783

EP - 3786

BT - ICPR 2012 - 21st International Conference on Pattern Recognition

T2 - 21st International Conference on Pattern Recognition, ICPR 2012

Y2 - 11 November 2012 through 15 November 2012

ER -

Glass object localization by joint inference of boundary and depth

Abstract

Publication series

Conference

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