dc.creator | González Díaz, Rocío | es |
dc.creator | Jiménez Rodríguez, María José | es |
dc.creator | Medrano Garfia, Belén | es |
dc.date.accessioned | 2019-02-27T10:54:06Z | |
dc.date.available | 2019-02-27T10:54:06Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | González Díaz, R., Jiménez Rodríguez, M.J. y Medrano Garfia, B. (2018). Topological tracking of connected components in image sequences. Journal of Computer and Systems Sciences, 95 (August 2018), 134-142. | |
dc.identifier.issn | 0022-0000 | es |
dc.identifier.uri | https://hdl.handle.net/11441/83553 | |
dc.description.abstract | Persistent homology provides information about the lifetime of homology
classes along a filtration of cell complexes. Persistence barcode is a graphi-
cal representation of such information. A filtration might be determined by
time in a set of spatiotemporal data, but classical methods for computing
persistent homology do not respect the fact that we can not move back-
wards in time. In this paper, taking as input a time-varying sequence of
two-dimensional (2D) binary digital images, we develop an algorithm for en-
coding, in the so-called spatiotemporal barcode, lifetime of connected compo-
nents (of either the foreground or background) that are moving in the image
sequence over time (this information may not coincide with the one provided
by the persistence barcode). This way, given a connected component at a
specific time in the sequence, we can track the component backwards in time
until the moment it was born, by what we call a spatiotemporal path. The
main contribution of this paper with respect to our previous works lies in a
new algorithm that computes spatiotemporal paths directly, valid for both
foreground and background and developed in a general context, setting the
ground for a future extension for tracking higher dimensional topological
features in nD binary digital image sequences. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad MTM2015-67072-P | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Journal of Computer and Systems Sciences, 95 (August 2018), 134-142. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Persistent homology | es |
dc.subject | Persistence barcodes | es |
dc.subject | Spatiotemporal data | es |
dc.subject | Binary digital image sequence analysis | es |
dc.title | Topological tracking of connected components in image sequences | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) | es |
dc.relation.projectID | MTM2015-67072-P | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0022000018300047 | es |
dc.identifier.doi | 10.1016/j.jcss.2017.12.005 | es |
idus.format.extent | 18 | es |
dc.journaltitle | Journal of Computer and Systems Sciences | es |
dc.publication.volumen | 95 | es |
dc.publication.issue | August 2018 | es |
dc.publication.initialPage | 134 | es |
dc.publication.endPage | 142 | es |
dc.contributor.funder | Ministerio de Economía y Competitividad (MINECO). España | |