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| Author(s): |
Paola Tatiana Llerena Valdivia
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) |
| Defense date: | 2018-05-17 |
| Examining board members: |
Maria Cristina Ferreira de Oliveira;
André Carlos Ponce de Leon Ferreira de Carvalho;
João Luiz Dihl Comba;
Nivan Roberto Ferreira Júnior;
José Gustavo de Souza Paiva
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| Advisor: | Luis Gustavo Nonato |
| Abstract | |
Signal processing is used in a wide variety of applications, ranging from digital image processing to biomedicine. Recently, some tools from signal processing have been extended to the context of graphs, allowing its use on irregular domains. Among others, the Fourier Transform and the Wavelet Transform have been adapted to such context. Graph signal processing (GSP) is a new field with many potential applications on data exploration. In this dissertation we show how tools from graph signal processing can be used for visual analysis. Specifically, we proposed a data filtering method, based on spectral graph filtering, that led to high quality visualizations which were attested qualitatively and quantitatively. On the other hand, we relied on the graph wavelet transform to enable the visual analysis of massive time-varying data revealing interesting phenomena and events. The proposed applications of GSP to visually analyze data are a first step towards incorporating the use of this theory into information visualization methods. Many possibilities from GSP can be explored by improving the understanding of static and time-varying phenomena that are yet to be uncovered. (AU) | |
| FAPESP's process: | 13/14089-3 - Multi-scale Visual Analysis Applied to Multidimensional Biological Data |
| Grantee: | Paola Tatiana Llerena Valdivia |
| Support Opportunities: | Scholarships in Brazil - Doctorate |