Video summarization using genetic algorithm and information theory

Tabrizi, Zeinab Zeinalpour; Minaei-Bidgoli, Behrouz; Fathi, M.

doi:10.1109/csicc.2009.5349317

Cited by 9 publications

(6 citation statements)

References 13 publications

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“…In this case the genetic algorithm has been used. Genetic Algorithm on video summarization [26] is an optimization algorithm to maximize the differences between the selected key frames. First the number of frames in the video summary result is defined.…”

Section: Evolutionary-computing Methodsmentioning

confidence: 99%

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The impact of colour visual attention for video summarization

Qian¹

2023

Preprint

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A High Definition visual attention based video summarization algorithm is proposed to extract feature frames and create a video summary. Specifically, the proposed framework is used as the basis for establishing whether or not there is a measurable impact on summaries constructed when choosing to incorporate visual attention mechanisms into the processing pipeline. The algorithm was assessed against manual human generated key-frame summaries presented with tested datasets from the Open Video Dataset (www.open-video.org). Of the frames selected by the algorithm, up to 68.1% were in agreement with the manual frame summaries depending on the category and length of the video. Specifically, a clear impact of agreement rate with the ground truth is demonstrated when including colour-attention models (in general) into the summarization framework, with the proposed colour-attention model achieving stronger agreement with human selected summaries, than other models from the literature.

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Section: Evolutionary-computing Methodsmentioning

confidence: 99%

“…The mutual information is a measure of the amount of information one random variable contains about another which also could be seen as a measure of the distance between two probability distributions [39,26]. Let be a finite set and X be a random variable taking values x in with distribution p(x) =Pr [X=x].…”

Section: Extract Attention Curvementioning

confidence: 99%

The impact of colour visual attention for video summarization

Qian¹

2023

Preprint

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“…A video usually have thousands of frames, and a lot of frames may be similar to adjacent ones [5].We should give special attention to those that are not too similar, so we first subsample the video at a lower rate.…”

Section: Feature Extractionmentioning

confidence: 99%

Video segmentation and summarization based on Genetic Algorithm

Yang

Wei

2011

2011 4th International Congress on Image and Signal Processing

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This paper presents a Binary Genetic Algorithms (BGA) based video summarization system. The similarity functions are first defined to evaluate segmentation, which are extremely expensive to be optimized with traditional methods. Then the system employs binary crossover and mutation operators to get the meaningful summary in a video search space. In order to test performance of the BGA method, we first compare the BGA method with Decimal Genetic Algorithms (DGA) method. The obtained results show that it is more quickly to find the best results for BGA than DGA. Second, the BGA method and the uniform approach have been compared. Experimental results show that the BGA method can capture more information than the uniform method and reduce redundancy.

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“…A video usually have thousands of frames, and a lot of adjacent ones may be similar [6].We should give more attention to those that are not too similar, so we first subsample the video frames at a lower rate and call this set of images A .…”

Section: Feature Extractionmentioning

confidence: 99%

A novel video summarization algorithm

Yang

Wei

2011

2011 International Conference on Multimedia Technology

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This paper presents a new genetic algorithm based method for video summarization. We pick out the least similar images from original video by measuring the differences with the technique of color histograms. Based on this reduced set, fitness function is defined for genetic algorithm to search the optimized frames. Experimental results show that the proposed method can capture more information than the traditional method and avoid redundancy. Moreover this algorithm has a distinct advantage in terms of time.

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Video summarization using genetic algorithm and information theory

Cited by 9 publications

References 13 publications

The impact of colour visual attention for video summarization

The impact of colour visual attention for video summarization

Video segmentation and summarization based on Genetic Algorithm

A novel video summarization algorithm

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