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Learning salient elements from videos using structural and temporal information

Grant number: 14/50135-2
Support type:Regular Research Grants
Duration: April 01, 2014 - July 31, 2016
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Cooperation agreement: CNRS
Principal Investigator:Roberto Marcondes Cesar Junior
Grantee:Roberto Marcondes Cesar Junior
Principal investigator abroad: Isabelle Bloch
Institution abroad: Laboratoire Traitement et Communication de l’Information (LTCI), France
Home Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:11/50761-2 - Models and methods of e-Science for life and agricultural sciences, AP.TEM

Abstract

This project proposes a novel framework to learn important elements from sports video sequences. The basic idea behind the proposal is that some key elements are salient in sports video and we would like to devise strategies for automatic learning them. For instance, in table tennis, despite the large possible variations in terms of camera pose, background, colors, etc, some key elements are consistently present in such videos: the table, two players moving around it, the rackets, the ball. The authors of this proposal are currently co-supervising a PhD project (Henrique Morimitsu, proc. FAPESP DR 12/09741-0 and BEPE 13/08258-7) which develops a novel framework for table and player detection in table tennis matches videos, which combines low-level features, temporal and structural information. The goal of this project submitted to CNRS/FAPESP is to go one step further by learning automatically the main elements in an unsupervised manner from video samples. Our idea is to use this proposal to recrute a Post-Doctoral researcher to develop the project (the PD scholarship will be submitted in due time in case this project is supported). (AU)

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)
MORIMITSU, HENRIQUE; BLOCH, ISABELLE; CESAR-, JR., ROBERTO M. Exploring structure for long-term tracking of multiple objects in sports videos. COMPUTER VISION AND IMAGE UNDERSTANDING, v. 159, n. SI, p. 89-104, JUN 2017. Web of Science Citations: 3.

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