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Feature-space-time Coherence with Heterogeneous Data

Grant number: 18/05668-3
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): May 01, 2018
Effective date (End): April 30, 2021
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal researcher:Anderson de Rezende Rocha
Grantee:Bahram Lavi Sefidgari
Home Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events, AP.TEM

Abstract

In this research, we are mainly aimed at answering the question of how to synchronize different sources of information (text content, posts, images and video recordings) in a comprehensive and coherent feature-space-time form for further inference, a problem we refer to as X-coherence. This question is precisely the first research question (Q1) of the DéjàVu thematic research project. The final expected outcomes are methods for performing X-coherence and combining different pieces of information in a comprehensive timeline for further inference and interpretation as well as solutions to transform heterogeneous sources of information into a unified representation.

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
RODRIGUES, CAROLINE MAZINI; SORIANO-VARGAS, AUREA; LAVI, BAHRAM; ROCHA, ANDERSON; DIAS, ZANONI. Manifold Learning for Real-World Event Understanding. IEEE Transactions on Information Forensics and Security, v. 16, p. 2957-2972, . (18/16548-9, 18/16214-3, 17/16246-0, 15/11937-9, 18/05668-3, 13/08293-7, 17/12646-3, 17/16871-1)
PADILHA, RAFAEL; ANDALO, FERNANDA A.; LAVI, BAHRAM; PEREIRA, LUIS A. M.; ROCHA, ANDERSON. Temporally sorting images from real-world events. PATTERN RECOGNITION LETTERS, v. 147, p. 212-219, . (17/21957-2, 17/12646-3, 18/05668-3, 18/16548-9)
PEIXOTO, BRUNO M.; LAVI, BAHRAM; DIAS, ZANONI; ROCHA, ANDERSON. Harnessing high-level concepts, visual, and auditory features for violence detection in videos. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, v. 78, . (17/12646-3, 18/05668-3)

Please report errors in scientific publications list by writing to: cdi@fapesp.br.