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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Bastos, R. & Dias, J. M. S. (2005). Fully automated texture tracking based on natural features extraction and template matching. In Lee, N. (Ed.), ACE '05: Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology. (pp. 180-183). Valencia: Association for Computing Machinery.
Exportar Referência (IEEE) 
R. Bastos and J. M. Dias,  "Fully automated texture tracking based on natural features extraction and template matching", in ACE '05: Proc. of the 2005 ACM SIGCHI Int. Conf. on Advances in computer entertainment technology, Lee, N., Ed., Valencia, Association for Computing Machinery, 2005, pp. 180-183
Exportar BibTeX 
@inproceedings{bastos2005_1734976348432,
	author = "Bastos, R. and Dias, J. M. S.",
	title = "Fully automated texture tracking based on natural features extraction and template matching",
	booktitle = "ACE '05: Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology",
	year = "2005",
	editor = "Lee, N.",
	volume = "",
	number = "",
	series = "",
	doi = "10.1145/1178477.1178502",
	pages = "180-183",
	publisher = "Association for Computing Machinery",
	address = "Valencia",
	organization = "Association for Computing Machinery",
	url = "https://dl.acm.org/doi/proceedings/10.1145/1178477"
}
Exportar RIS 
TY  - CPAPER
TI  - Fully automated texture tracking based on natural features extraction and template matching
T2  - ACE '05: Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology
AU  - Bastos, R.
AU  - Dias, J. M. S.
PY  - 2005
SP  - 180-183
DO  - 10.1145/1178477.1178502
CY  - Valencia
UR  - https://dl.acm.org/doi/proceedings/10.1145/1178477
AB  - In this work we propose a novel approach to real-time texture tracking and registration, based on natural feature extraction from planar objects and template matching, Our method is oriented to planar objects with arbitrary textures but with rectangular topologies and well contrasted contours and does not require any external fiducial marker, either for the set-up or the tracking phases. Once the initial pose condition is obtained, previous planar object information is used to compute subsequent planar object's pose, so that the time coherence of the input video stream is exploited. Our system is completely automated and produces real-time efficient tracking which can be applied to entertainment AR applications and other. The paper discusses also the novelty of the approach, in relation to other existing texture tracking algorithms.

ER  -