GLoG: Laplacian of Gaussian for Spatial Pattern Detection in Spatio-Temporal Data

Autor(es)

Nonato, Luis Gustavo ^[1] ; do Carmo, Fabiano Petronetto ^[2] ; Silva, Claudio T. ^[3]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, BR-05508220 Sao Paulo - Brazil

^[2] Univ Fed Espirito Santo, BR-29075910 Espirito Santo - Brazil

^[3] NYU, 550 1St Ave, New York, NY 10003 - USA

• Tipo de documento: Artigo Científico
• Fonte: IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS; v. 27, n. 8, p. 3481-3492, AUG 1 2021.
• Citações Web of Science: 0

Resumo

Boundary detection has long been a fundamental tool for image processing and computer vision, supporting the analysis of static and time-varying data. In this work, we built upon the theory of Graph Signal Processing to propose a novel boundary detection filter in the context of graphs, having as main application scenario the visual analysis of spatio-temporal data. More specifically, we propose the equivalent for graphs of the so-called Laplacian of Gaussian edge detection filter, which is widely used in image processing. The proposed filter is able to reveal interesting spatial patterns while still enabling the definition of entropy of time slices. The entropy reveals the degree of randomness of a time slice, helping users to identify expected and unexpected phenomena over time. The effectiveness of our approach appears in applications involving synthetic and real data sets, which show that the proposed methodology is able to uncover interesting spatial and temporal phenomena. The provided examples and case studies make clear the usefulness of our approach as a mechanism to support visual analytic tasks involving spatio-temporal data. (AU)

• Processo FAPESP: 14/12236-1 - AnImaLS: Anotação de Imagem em Larga Escala: o que máquinas e especialistas podem aprender interagindo?
• Beneficiário: Alexandre Xavier Falcão
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria
• Beneficiário: Francisco Louzada Neto
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
• Processo FAPESP: 16/04391-2 - Operadores de morfologia matemática para a análise visual de dados urbanos
• Beneficiário: Fábio Augusto Salve Dias
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Pós-Doutorado