Personalized Summarization of Broadcasted Soccer Videos with Adaptive Fast-Forwarding

Chen, Fan; Vleeschouwer, Christophe De

doi:10.1007/978-3-319-03892-6_1

Cited by 3 publications

(9 citation statements)

References 11 publications

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“…Olsen and Moon [39] described how the user interaction of previous viewers could be used to create a personalized video summarization, computing more interesting plays in a game. Chen et al [40,41] produced a hybrid personalized video summarization framework by summarizing broadcast soccer video that combines content truncation and adaptive fast forwarding. Kao et al proposed a personal video summarization system that integrates the global positioning system and the radio frequency identification information for marathon activities [42].…”

Section: Personalized Sport Highlightsmentioning

confidence: 99%

“…In personalized video summary, fast forward is used in sports videos, where each viewer wants to watch the main phases of the match that are of interest to him according to his preferences, while also having a brief overview of the remaining phases that are not as interesting or important to him. Chen and Vleeschouwer [41] proposed a personalized video summarization framework for soccer video broadcasts with adaptive fast forwarding where efficient resource allocation selection selects the optimal combination of candidate summaries.…”

Section: Type Of Personalized Summarymentioning

confidence: 99%

“…The summaries presented in [12][13][14]17,20,22,25,27,30,31,33,34,45,47,51,54,55,[57][58][59][60][63][64][65][67][68][69][70][71]73] are not domain specific. The types of domains found in the literature are Personal Videos [52,53], Movies / serial clips [19,28,29,35,49], Sports Videos [18,35,[37][38][39][40][41][42][43][44],…”

Section: Video Domainmentioning

confidence: 99%

“…A summary was prepared using periodic sampling with a constant segment length and interval, a different kind of summary was created using the proposed method based on the behavior of another individual, and a summary was made using the proposed method based on the subject's behavioral data. In the study by [41], two subjective evaluations were carried out. The first evaluation focused on determining the appropriate playback speeds.…”

Section: Evaluating Personalized Fast Forwardmentioning

confidence: 99%

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Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets

Peronikolis,

Panagiotakis

2024

Preprint

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In recent years, the scientific and technological developments led to an explosion of available videos on the web, increasing the necessity of fast and effective video analysis and summarization. Video summarization methods aim to generate a synopsis by selecting the most informative parts of the video content. The user’s personal preferences, often involved in the expected results, should be taken into account in the video summaries. In this paper, we provide the first comprehensive survey on personalized video summarization relevant to the techniques and datasets used. In this context, we classify and review personalized video summary techniques based on the type of personalized summary, on criteria, on the video domain, on the source of information, on the time of summarization, and on the machine learning technique. Depending on the type of methodology used by the personalized video summarization techniques for the summary production process, we classify the techniques into five major categories, which are feature-based video summarization, key frame selection, shot selection-based approach, video summarization using trajectory analysis, and personalized video summarization using clustering. We also compare personalized video summarization methods and present 37 datasets used to evaluate personalized video summarization methods. Finally, we analyze opportunities and challenges in the field and suggest innovative research lines.

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Section: Personalized Sport Highlightsmentioning

confidence: 99%

Section: Type Of Personalized Summarymentioning

confidence: 99%

Section: Video Domainmentioning

confidence: 99%

Section: Evaluating Personalized Fast Forwardmentioning

confidence: 99%

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Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets

Peronikolis,

Panagiotakis

2024

Preprint

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show abstract

“…Olsen and Moon [40] described how the user interaction of previous viewers could be used to create a personalized video summarization, computing more interesting plays in a game. Chen et al [41,42] produced a hybrid personalized video summarization framework by summarizing a broadcast soccer video that combines content truncation and adaptive fast forwarding. Kao et al proposed a personal video summarization system that integrates the global positioning system and the radio frequency identification information for marathon activities [43].…”

Section: Personalized Sport Highlightsmentioning

confidence: 99%

Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets

Peronikolis,

Panagiotakis

2024

Applied Sciences

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In recent years, the scientific and technological developments have led to an explosion of available videos on the web, increasing the necessity of fast and effective video analysis and summarization. Video summarization methods aim to generate a synopsis by selecting the most informative parts of the video content. The user’s personal preferences, often involved in the expected results, should be taken into account in the video summaries. In this paper, we provide the first comprehensive survey on personalized video summarization relevant to the techniques and datasets used. In this context, we classify and review personalized video summary techniques based on the type of personalized summary, on the criteria, on the video domain, on the source of information, on the time of summarization, and on the machine learning technique. Depending on the type of methodology used by the personalized video summarization techniques for the summary production process, we classify the techniques into five major categories, which are feature-based video summarization, keyframe selection, shot selection-based approach, video summarization using trajectory analysis, and personalized video summarization using clustering. We also compare personalized video summarization methods and present 37 datasets used to evaluate personalized video summarization methods. Finally, we analyze opportunities and challenges in the field and suggest innovative research lines.

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The Shape of the Game

Coimbra

Neves

Telea

et al. 2018

2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)

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Personalized Summarization of Broadcasted Soccer Videos with Adaptive Fast-Forwarding

Cited by 3 publications

References 11 publications

Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets

Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets

Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets

The Shape of the Game

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