Indoor scene segmentation using a structured light sensor

Nathan Silberman; Rob Fergus

doi:10.1109/ICCVW.2011.6130298

Indoor scene segmentation using a structured light sensor

Nathan Silberman, Rob Fergus

Computer Science

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

Abstract

In this paper we explore how a structured light depth sensor, in the form of the Microsoft Kinect, can assist with indoor scene segmentation. We use a CRF-based model to evaluate a range of different representations for depth information and propose a novel prior on 3D location. We introduce a new and challenging indoor scene dataset, complete with accurate depth maps and dense label coverage. Evaluating our model on this dataset reveals that the combination of depth and intensity images gives dramatic performance gains over intensity images alone. Our results clearly demonstrate the utility of structured light sensors for scene understanding.

Original language	English (US)
Title of host publication	2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Pages	601-608
Number of pages	8
DOIs	https://doi.org/10.1109/ICCVW.2011.6130298
State	Published - 2011
Event	2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 - Barcelona, Spain Duration: Nov 6 2011 → Nov 13 2011

Publication series

Name	Proceedings of the IEEE International Conference on Computer Vision

Other

Other	2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Country/Territory	Spain
City	Barcelona
Period	11/6/11 → 11/13/11

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition

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10.1109/ICCVW.2011.6130298

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Silberman, N & Fergus, R 2011, Indoor scene segmentation using a structured light sensor. in 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011., 6130298, Proceedings of the IEEE International Conference on Computer Vision, pp. 601-608, 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011, Barcelona, Spain, 11/6/11. https://doi.org/10.1109/ICCVW.2011.6130298

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title = "Indoor scene segmentation using a structured light sensor",

abstract = "In this paper we explore how a structured light depth sensor, in the form of the Microsoft Kinect, can assist with indoor scene segmentation. We use a CRF-based model to evaluate a range of different representations for depth information and propose a novel prior on 3D location. We introduce a new and challenging indoor scene dataset, complete with accurate depth maps and dense label coverage. Evaluating our model on this dataset reveals that the combination of depth and intensity images gives dramatic performance gains over intensity images alone. Our results clearly demonstrate the utility of structured light sensors for scene understanding.",

author = "Nathan Silberman and Rob Fergus",

year = "2011",

doi = "10.1109/ICCVW.2011.6130298",

language = "English (US)",

isbn = "9781467300629",

series = "Proceedings of the IEEE International Conference on Computer Vision",

pages = "601--608",

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note = "2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 ; Conference date: 06-11-2011 Through 13-11-2011",

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AB - In this paper we explore how a structured light depth sensor, in the form of the Microsoft Kinect, can assist with indoor scene segmentation. We use a CRF-based model to evaluate a range of different representations for depth information and propose a novel prior on 3D location. We introduce a new and challenging indoor scene dataset, complete with accurate depth maps and dense label coverage. Evaluating our model on this dataset reveals that the combination of depth and intensity images gives dramatic performance gains over intensity images alone. Our results clearly demonstrate the utility of structured light sensors for scene understanding.

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BT - 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011

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ER -

Indoor scene segmentation using a structured light sensor

Abstract

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