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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

VISON: Video Summarization for ONline applications

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Autor(es):
Almeida, Jurandy [1] ; Leite, Neucimar J. [1] ; Torres, Ricardo da S. [1]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Campinas UNICAMP, Inst Comp, BR-13083852 Campinas, SP - Brazil
Número total de Afiliações: 1
Tipo de documento: Artigo Científico
Fonte: PATTERN RECOGNITION LETTERS; v. 33, n. 4, SI, p. 397-409, MAR 2012.
Citações Web of Science: 59
Resumo

Recent advances in technology have increased the availability of video data, creating a strong requirement for efficient systems to manage those materials. Making efficient use of video information requires that data to be accessed in a user-friendly way. This has been the goal of a quickly evolving research area known as video summarization. Most of existing techniques to address the problem of summarizing a video sequence have focused on the uncompressed domain. However, decoding and analyzing of a video sequence are two extremely time-consuming tasks. Thus, video summaries are usually produced off-line, penalizing any user interaction. The lack of customization is very critical, as users often have different demands and resources. Since video data are usually available in compressed form, it is desirable to directly process video material without decoding. In this paper, we present VISON, a novel approach for video summarization that works in the compressed domain and allows user interaction. The proposed method is based on both exploiting visual features extracted from the video stream and on using a simple and fast algorithm to summarize the video content. Results from a rigorous empirical comparison with a subjective evaluation show that our technique produces video summaries with high quality relative to the state-of-the-art solutions and in a computational time that makes it suitable for online usage. (C) 2011 Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 08/50837-6 - Busca por similaridade em espaços métricos utilizando técnicas de agrupamento de dados
Beneficiário:Jurandy Gomes de Almeida Junior
Linha de fomento: Bolsas no Brasil - Doutorado
Processo FAPESP: 09/18438-7 - Classificação e busca em grande escala para dados complexos
Beneficiário:Ricardo da Silva Torres
Linha de fomento: Auxílio à Pesquisa - Regular
Processo FAPESP: 07/52015-0 - Métodos de aproximação para computação visual
Beneficiário:Jorge Stolfi
Linha de fomento: Auxílio à Pesquisa - Temático