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Reconstructing a convex polygon from its ω -cloud. / Arseneva, Elena; Bose, Prosenjit; De Carufel, Jean Lou; Verdonschot, Sander.

Computer Science – Theory and Applications - 14th International Computer Science Symposium in Russia, CSR 2019, Proceedings. ред. / René van Bevern; Gregory Kucherov. Springer Nature, 2019. стр. 25-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11532 LNCS).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Arseneva, E, Bose, P, De Carufel, JL & Verdonschot, S 2019, Reconstructing a convex polygon from its ω -cloud. в R van Bevern & G Kucherov (ред.), Computer Science – Theory and Applications - 14th International Computer Science Symposium in Russia, CSR 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 11532 LNCS, Springer Nature, стр. 25-37, 14th International Computer Science Symposium in Russia, CSR 2019, Novosibirsk, Российская Федерация, 1/07/19. https://doi.org/10.1007/978-3-030-19955-5_3

APA

Arseneva, E., Bose, P., De Carufel, J. L., & Verdonschot, S. (2019). Reconstructing a convex polygon from its ω -cloud. в R. van Bevern, & G. Kucherov (Ред.), Computer Science – Theory and Applications - 14th International Computer Science Symposium in Russia, CSR 2019, Proceedings (стр. 25-37). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11532 LNCS). Springer Nature. https://doi.org/10.1007/978-3-030-19955-5_3

Vancouver

Arseneva E, Bose P, De Carufel JL, Verdonschot S. Reconstructing a convex polygon from its ω -cloud. в van Bevern R, Kucherov G, Редакторы, Computer Science – Theory and Applications - 14th International Computer Science Symposium in Russia, CSR 2019, Proceedings. Springer Nature. 2019. стр. 25-37. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-19955-5_3

Author

Arseneva, Elena ; Bose, Prosenjit ; De Carufel, Jean Lou ; Verdonschot, Sander. / Reconstructing a convex polygon from its ω -cloud. Computer Science – Theory and Applications - 14th International Computer Science Symposium in Russia, CSR 2019, Proceedings. Редактор / René van Bevern ; Gregory Kucherov. Springer Nature, 2019. стр. 25-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{e898b7347778440899e3d191ea8a53d3,
title = "Reconstructing a convex polygon from its ω -cloud",
abstract = "An ω -wedge is the closed set of points contained between two rays that are emanating from a single point (the apex), and are separated by an angle ω< π. Given a convex polygon P, we place the ω -wedge such that P is inside the wedge and both rays are tangent to P. The set of apex positions of all such placements of the ω -wedge is called the ω -cloud of P. We investigate reconstructing a polygon P from its ω -cloud. Previous work on reconstructing P from probes with the ω -wedge required knowledge of the points of tangency between P and the two rays of the ω -wedge in addition to the location of the apex. Here we consider the setting where the maximal ω -cloud alone is given. We give two conditions under which it uniquely defines P: (i) when ω< π is fixed/given, or (ii) when what is known is that ω< π/ 2. We show that if neither of these two conditions hold, then P may not be unique. We show that, when the uniqueness conditions hold, the polygon P can be reconstructed in O(n) time with O(1) working space in addition to the input, where n is the number of arcs in the input ω -cloud.",
keywords = "TRIANGLES, SHAPE",
author = "Elena Arseneva and Prosenjit Bose and {De Carufel}, {Jean Lou} and Sander Verdonschot",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-19955-5_3",
language = "English",
isbn = "9783030199548",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "25--37",
editor = "{van Bevern}, Ren{\'e} and Gregory Kucherov",
booktitle = "Computer Science – Theory and Applications - 14th International Computer Science Symposium in Russia, CSR 2019, Proceedings",
address = "Germany",
note = "14th International Computer Science Symposium in Russia, CSR 2019 ; Conference date: 01-07-2019 Through 05-07-2019",

}

RIS

TY - GEN

T1 - Reconstructing a convex polygon from its ω -cloud

AU - Arseneva, Elena

AU - Bose, Prosenjit

AU - De Carufel, Jean Lou

AU - Verdonschot, Sander

PY - 2019/1/1

Y1 - 2019/1/1

N2 - An ω -wedge is the closed set of points contained between two rays that are emanating from a single point (the apex), and are separated by an angle ω< π. Given a convex polygon P, we place the ω -wedge such that P is inside the wedge and both rays are tangent to P. The set of apex positions of all such placements of the ω -wedge is called the ω -cloud of P. We investigate reconstructing a polygon P from its ω -cloud. Previous work on reconstructing P from probes with the ω -wedge required knowledge of the points of tangency between P and the two rays of the ω -wedge in addition to the location of the apex. Here we consider the setting where the maximal ω -cloud alone is given. We give two conditions under which it uniquely defines P: (i) when ω< π is fixed/given, or (ii) when what is known is that ω< π/ 2. We show that if neither of these two conditions hold, then P may not be unique. We show that, when the uniqueness conditions hold, the polygon P can be reconstructed in O(n) time with O(1) working space in addition to the input, where n is the number of arcs in the input ω -cloud.

AB - An ω -wedge is the closed set of points contained between two rays that are emanating from a single point (the apex), and are separated by an angle ω< π. Given a convex polygon P, we place the ω -wedge such that P is inside the wedge and both rays are tangent to P. The set of apex positions of all such placements of the ω -wedge is called the ω -cloud of P. We investigate reconstructing a polygon P from its ω -cloud. Previous work on reconstructing P from probes with the ω -wedge required knowledge of the points of tangency between P and the two rays of the ω -wedge in addition to the location of the apex. Here we consider the setting where the maximal ω -cloud alone is given. We give two conditions under which it uniquely defines P: (i) when ω< π is fixed/given, or (ii) when what is known is that ω< π/ 2. We show that if neither of these two conditions hold, then P may not be unique. We show that, when the uniqueness conditions hold, the polygon P can be reconstructed in O(n) time with O(1) working space in addition to the input, where n is the number of arcs in the input ω -cloud.

KW - TRIANGLES

KW - SHAPE

UR - http://www.scopus.com/inward/record.url?scp=85068603963&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/reconstructing-convex-polygon-%CF%89-cloud

U2 - 10.1007/978-3-030-19955-5_3

DO - 10.1007/978-3-030-19955-5_3

M3 - Conference contribution

AN - SCOPUS:85068603963

SN - 9783030199548

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 25

EP - 37

BT - Computer Science – Theory and Applications - 14th International Computer Science Symposium in Russia, CSR 2019, Proceedings

A2 - van Bevern, René

A2 - Kucherov, Gregory

PB - Springer Nature

T2 - 14th International Computer Science Symposium in Russia, CSR 2019

Y2 - 1 July 2019 through 5 July 2019

ER -

ID: 48856545