caa a22 4500 605447063 CHVBK 20210128100130.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s11042-014-2126-8 doi (NATIONALLICENCE)springer-10.1007/s11042-014-2126-8 An iteratively reweighting algorithm for dynamic video summarization [Elektronische Daten] [Pei Dong, Yong Xia, Shanshan Wang, Li Zhuo, David Feng] Information explosion has imposed unprecedented challenges on the conventional ways of video data consumption. Hence providing condensed and meaningful video summary to viewers has been recognized as a beneficial and attractive research in the multimedia community in recent years. Analyzing both the visual and textual modalities proves essential for an automatic video summarizer to pick up important contents from a video. However, most established studies in this direction either use heuristic rules or rely on simple ways of text analysis. This paper proposes an iteratively reweighting dynamic video summarization (IRDVS) algorithm based on the joint and adaptive use of the visual modality and accompanying subtitles. The proposed algorithm takes advantage of our developed SEmantic inDicator of videO seGment (SEDOG) feature for exploring the most representative concepts for describing the video. Meanwhile, the iteratively reweighting scheme effectively updates the dynamic surrogate of the original video by combining the high-level features in an adaptive manner. The proposed algorithm has been compared to four state-of-the-art video summarization approaches, namely the speech transcript-based (STVS) algorithm, attention model-based (AMVS) algorithm, sparse dictionary selection-based (DSVS) algorithm and heterogeneity image patch index-based (HIPVS) algorithm, on different video genres, including documentary, movie and TV news. Our results show that the proposed IRDVS algorithm can produce summarized videos with better quality. Springer Science+Business Media New York, 2014 Video summarization nationallicence Semantic indicator of video segment (SEDOG) nationallicence Iterative weight estimation nationallicence Multimodal features nationallicence Saliency ranking nationallicence Dong Pei Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Sydney, Australia aut Xia Yong Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Sydney, Australia aut Wang Shanshan Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Sydney, Australia aut Zhuo Li Signal and Information Processing Laboratory, Beijing University of Technology, 100124, Beijing, China aut Feng David Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Sydney, Australia aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/21(2015-11-01), 9449-9473 1380-7501 74:21<9449 2015 74 11042 https://doi.org/10.1007/s11042-014-2126-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-014-2126-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Dong Pei Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Sydney, Australia aut NATIONALLICENCE 700 1- Xia Yong Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Sydney, Australia aut NATIONALLICENCE 700 1- Wang Shanshan Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Sydney, Australia aut NATIONALLICENCE 700 1- Zhuo Li Signal and Information Processing Laboratory, Beijing University of Technology, 100124, Beijing, China aut NATIONALLICENCE 700 1- Feng David Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Sydney, Australia aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/21(2015-11-01), 9449-9473 1380-7501 74:21<9449 2015 74 11042