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Titolo:
Automatic video parsing using shot boundary detection and camera operationanalysis
Autore:
Lee, MS; Yang, YM; Lee, SW;
Indirizzi:
Korea Univ, Ctr Artificial Vis Res, Seongbuk Ku, Seoul 136701, South KoreaKorea Univ Seoul South Korea 136701 ongbuk Ku, Seoul 136701, South Korea
Titolo Testata:
PATTERN RECOGNITION
fascicolo: 3, volume: 34, anno: 2001,
pagine: 711 - 719
SICI:
0031-3203(200103)34:3<711:AVPUSB>2.0.ZU;2-L
Fonte:
ISI
Lingua:
ENG
Keywords:
automatic video parsing; content-based retrieval; video indexing; shot boundary detection; camera operation analysis; multilayer perceptron;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
9
Recensione:
Indirizzi per estratti:
Indirizzo: Lee, SW Korea Univ, Ctr Artificial Vis Res, Seongbuk Ku, Anam Dong, Seoul 136701, South Korea Korea Univ Anam Dong Seoul South Korea 136701 136701, South Korea
Citazione:
M.S. Lee et al., "Automatic video parsing using shot boundary detection and camera operationanalysis", PATT RECOG, 34(3), 2001, pp. 711-719

Abstract

In this paper, we present an efficient video parsing method for automatingcontent-based video indexing and retrieval using shot boundary detection and camera operation analysis techniques. In the shot boundary detection, the local color information is used in order to eliminate the false detectioncaused by an abrupt change of illumination such as camera flash or thunder. In order to reduce the computation time in the shot boundary detection, an adaptive time window is applied to this procedure. Local spatio-temporal images and multilayer perceptron are used for analyzing camera operations. The proposed method uses a learning algorithm with spatio-temporal information in the frame and does not process the entire video image to reduce the processing time. In order to verify the performance of the proposed automatic video parsing method, experiments have been carried out with a video database that includes news, documentary and movie. Experimental results demonstrate the efficiency of the proposed video parsing technique. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 03/07/20 alle ore 22:04:47