The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Este artigo apresenta um esquema de classificação de tomadas comerciais que combina recursos visuais e textuais bem projetados para detectar automaticamente comerciais de TV. Para identificar a diferença inerente entre comerciais e programas gerais, é proposto um descritor textual especial de nível médio, com o objetivo de capturar as propriedades espaço-temporais dos videotextos típicos dos comerciais. Além disso, introduzimos um método de combinação baseado em aprendizagem em conjunto, denominado Co-AdaBoost, para explorar interativamente as relações intrínsecas entre os recursos visuais e textuais empregados.
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Nan LIU, Yao ZHAO, Zhenfeng ZHU, Rongrong NI, "Commercial Shot Classification Based on Multiple Features Combination" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 9, pp. 2651-2655, September 2010, doi: 10.1587/transinf.E93.D.2651.
Abstract: This paper presents a commercial shot classification scheme combining well-designed visual and textual features to automatically detect TV commercials. To identify the inherent difference between commercials and general programs, a special mid-level textual descriptor is proposed, aiming to capture the spatio-temporal properties of the video texts typical of commercials. In addition, we introduce an ensemble-learning based combination method, named Co-AdaBoost, to interactively exploit the intrinsic relations between the visual and textual features employed.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2651/_p
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@ARTICLE{e93-d_9_2651,
author={Nan LIU, Yao ZHAO, Zhenfeng ZHU, Rongrong NI, },
journal={IEICE TRANSACTIONS on Information},
title={Commercial Shot Classification Based on Multiple Features Combination},
year={2010},
volume={E93-D},
number={9},
pages={2651-2655},
abstract={This paper presents a commercial shot classification scheme combining well-designed visual and textual features to automatically detect TV commercials. To identify the inherent difference between commercials and general programs, a special mid-level textual descriptor is proposed, aiming to capture the spatio-temporal properties of the video texts typical of commercials. In addition, we introduce an ensemble-learning based combination method, named Co-AdaBoost, to interactively exploit the intrinsic relations between the visual and textual features employed.},
keywords={},
doi={10.1587/transinf.E93.D.2651},
ISSN={1745-1361},
month={September},}
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TY - JOUR
TI - Commercial Shot Classification Based on Multiple Features Combination
T2 - IEICE TRANSACTIONS on Information
SP - 2651
EP - 2655
AU - Nan LIU
AU - Yao ZHAO
AU - Zhenfeng ZHU
AU - Rongrong NI
PY - 2010
DO - 10.1587/transinf.E93.D.2651
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2010
AB - This paper presents a commercial shot classification scheme combining well-designed visual and textual features to automatically detect TV commercials. To identify the inherent difference between commercials and general programs, a special mid-level textual descriptor is proposed, aiming to capture the spatio-temporal properties of the video texts typical of commercials. In addition, we introduce an ensemble-learning based combination method, named Co-AdaBoost, to interactively exploit the intrinsic relations between the visual and textual features employed.
ER -