Standard
3D inference and modelling for video retrieval. / Zhou, Huiyu; Sadka, Abdul
; Jiang, Richard M. WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services. 2008. p. 84-87 4556889 (WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Zhou, H, Sadka, A
& Jiang, RM 2008,
3D inference and modelling for video retrieval. in
WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services., 4556889, WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services, pp. 84-87, 9th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2008, Klagenfurt, Austria,
7/05/08.
https://doi.org/10.1109/WIAMIS.2008.37APA
Vancouver
Zhou H, Sadka A
, Jiang RM.
3D inference and modelling for video retrieval. In WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services. 2008. p. 84-87. 4556889. (WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services). doi: 10.1109/WIAMIS.2008.37
Author
Zhou, Huiyu ; Sadka, Abdul
; Jiang, Richard M. /
3D inference and modelling for video retrieval. WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services. 2008. pp. 84-87 (WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services).
Bibtex
@inproceedings{ee51edaa76f441b79e8f55610cd55b37,
title = "3D inference and modelling for video retrieval",
abstract = "A new scheme is proposed for extracting planar surfaces from 2D image sequences. We firstly perform feature correspondence over two neighboring frames, followed by the estimation of disparity and depth maps, provided a calibrated camera. We then apply iterative Random Sample Consensus (RANSAC) plane fitting to the generated 3D points to find a dominant plane in a maximum likelihood estimation style. Object points on or off this dominant plane are determined by measuring their Euclidean distance to the plane. Experimental work shows that the proposed scheme leads to better plane fitting results than the classical RANSAC method.",
author = "Huiyu Zhou and Abdul Sadka and Jiang, {Richard M.}",
year = "2008",
month = sep,
day = "19",
doi = "10.1109/WIAMIS.2008.37",
language = "English",
isbn = "9780769531304",
series = "WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services",
pages = "84--87",
booktitle = "WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services",
note = "9th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2008 ; Conference date: 07-05-2008 Through 09-05-2008",
}
RIS
TY - GEN
T1 - 3D inference and modelling for video retrieval
AU - Zhou, Huiyu
AU - Sadka, Abdul
AU - Jiang, Richard M.
PY - 2008/9/19
Y1 - 2008/9/19
N2 - A new scheme is proposed for extracting planar surfaces from 2D image sequences. We firstly perform feature correspondence over two neighboring frames, followed by the estimation of disparity and depth maps, provided a calibrated camera. We then apply iterative Random Sample Consensus (RANSAC) plane fitting to the generated 3D points to find a dominant plane in a maximum likelihood estimation style. Object points on or off this dominant plane are determined by measuring their Euclidean distance to the plane. Experimental work shows that the proposed scheme leads to better plane fitting results than the classical RANSAC method.
AB - A new scheme is proposed for extracting planar surfaces from 2D image sequences. We firstly perform feature correspondence over two neighboring frames, followed by the estimation of disparity and depth maps, provided a calibrated camera. We then apply iterative Random Sample Consensus (RANSAC) plane fitting to the generated 3D points to find a dominant plane in a maximum likelihood estimation style. Object points on or off this dominant plane are determined by measuring their Euclidean distance to the plane. Experimental work shows that the proposed scheme leads to better plane fitting results than the classical RANSAC method.
U2 - 10.1109/WIAMIS.2008.37
DO - 10.1109/WIAMIS.2008.37
M3 - Conference contribution/Paper
AN - SCOPUS:51749085862
SN - 9780769531304
T3 - WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services
SP - 84
EP - 87
BT - WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services
T2 - 9th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2008
Y2 - 7 May 2008 through 9 May 2008
ER -
