Topological tracking of connected components in image sequences
| Autor: | Belen Medrano, Rocio Gonzalez-Diaz, María José Jiménez |
|---|---|
| Přispěvatelé: | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Ministerio de Economía y Competitividad (MINECO). España |
| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Computer Networks and Communications Computer science Computer Vision and Pattern Recognition (cs.CV) Computer Science - Computer Vision and Pattern Recognition Context (language use) 02 engineering and technology Topology Barcode 01 natural sciences Theoretical Computer Science law.invention Digital image 020901 industrial engineering & automation Persistence barcodes law Encoding (memory) Spatiotemporal data Persistent homology 0101 mathematics Connected component Sequence Applied Mathematics 010102 general mathematics Computational Theory and Mathematics Path (graph theory) Binary digital image sequence analysis |
| Zdroj: | idUS: Depósito de Investigación de la Universidad de Sevilla Universidad de Sevilla (US) idUS. Depósito de Investigación de la Universidad de Sevilla instname |
| ISSN: | 2015-6707 |
| Popis: | 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. Ministerio de Economía y Competitividad MTM2015-67072-P |
| Databáze: | OpenAIRE |
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