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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Temporally sorting images from real-world events

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Author(s):
Padilha, Rafael [1] ; Andalo, Fernanda A. [1] ; Lavi, Bahram [1] ; Pereira, Luis A. M. [1] ; Rocha, Anderson [1]
Total Authors: 5
Affiliation:
[1] Univ Estadual Campinas, Inst Comp, Campinas, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: PATTERN RECOGNITION LETTERS; v. 147, p. 212-219, JUL 2021.
Web of Science Citations: 2
Abstract

As smartphones become ubiquitous in modern life, every major event \& mdash; from musical concerts to ter-rorist attempts \& mdash; is massively captured by multiple devices and instantly uploaded to the Internet. Once shared through social media, the chronological order between available media pieces cannot be reliably recovered, hindering the understanding and reconstruction of that event. In this work, we propose data -driven methods for temporally sorting images originated from heterogeneous sources and captured from distinct angles, viewpoints, and moments. We model the chronological sorting task as an ensemble of binary classifiers whose answers are combined hierarchically to estimate an image \& rsquo;s temporal position within the duration of the event. We evaluate our method on images from the Notre-Dame Catedral fire and the Grenfell Tower fire events and discuss research challenges for analyzing data from real-world forensic events. Finally, we employ visualization techniques to understand what our models have learned, offering additional insights to the problem. (c) 2021 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 17/21957-2 - Learning Visual Clues of the Passage of Time
Grantee:Rafael Soares Padilha
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events
Grantee:Anderson de Rezende Rocha
Support type: Research Projects - Thematic Grants
FAPESP's process: 18/05668-3 - Feature-space-time Coherence with Heterogeneous Data
Grantee:Bahram Lavi Sefidgari
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 18/16548-9 - Learning Visual Clues of the Passage of Time
Grantee:Luis Augusto Martins Pereira
Support type: Scholarships in Brazil - Post-Doctorate