VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method

Avila, Sandra; Lopes, Amauri; Luz, Antonio da; Araújo, Arnaldo de Albuquerque

doi:10.1016/j.patrec.2010.08.004

Cited by 568 publications

(520 citation statements)

References 41 publications

(57 reference statements)

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“…These are then described with a linear model with the addition of noise. As reported, the method obtains results comparable to other methods, such as [2].…”

Section: Related Worksupporting

confidence: 73%

“…For evaluation, we used the VSUMM database and provided therein summarization of different videos [2,22]. Such an approach has been undertaken by many researchers and allows qualitative evaluation and comparison among a group of video summarization methods.…”

Section: Resultsmentioning

confidence: 99%

“…A method, called VSUMM, is proposed in the paper by de Avila et al [2]. Their approach is based on computation of color histograms from frames acquired from a video stream one per second, then clustered with the k-means method.…”

Section: Related Workmentioning

confidence: 99%

“…Nevertheless, if there is additional knowledge of a signal type, then methods that compute specific features can be more discriminative but only for this specific type of a signal. This happens with color histograms, frequently used in video shot detection [2,7,35]. Such methods will not work with monochrome or hyperspectral images, though.…”

Section: System Architecture and Basic Concepts Of The Tensor Stream mentioning

confidence: 99%

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Tensor-Based Shot Boundary Detection in Video Streams

Cyganek

Woźniak

2017

New Gener. Comput.

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This paper presents a method for content change detection in multidimensional video signals. Video frames are represented as tensors of order consistent with signal dimensions. The method operates on unprocessed signals and no special feature extraction is assumed. The dynamic tensor analysis method is used to build a tensor model from the stream. Each new datum in the stream is then compared to the model with the proposed concept drift detector. If it fits, then a model is updated. Otherwise, a model is rebuilt, starting from that datum, and the signal shot is recorded. The proposed fast tensor decomposition algorithm allows efficient operation compared to the standard tensor decomposition method. Experimental results show many useful properties of the method, as well as its potential further extensions and applications.

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“…These are then described with a linear model with the addition of noise. As reported, the method obtains results comparable to other methods, such as [2].…”

Section: Related Worksupporting

confidence: 73%

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: System Architecture and Basic Concepts Of The Tensor Stream mentioning

confidence: 99%

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Tensor-Based Shot Boundary Detection in Video Streams

Cyganek

Woźniak

2017

New Gener. Comput.

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“…To this end, we have created a dataset where we seek the most interesting parts of a movie, based on similarity to generic movie trailers, namely the IMPART-AUTH Movie Trailer Dataset. This dataset has been created to provide a movie summarization scenario, since other publicly available datasets specially created for video summarization (e.g., [42]) provide simplistic or unrealistic video summarization scenarios. In the case of movies, video shots appearing in movie trailers are good examples of salient video segments, since they have been specially edited, in order to catch the viewer attention and, at the same time, to describe the movie plot.…”

Section: Experiments On Video Summarizationmentioning

confidence: 99%