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The impact of colour visual attention for video summarization.

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thesis
posted on 23.05.2021, 13:23 by Yiming Qian
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.

History

Degree

Master of Applied Science

Program

Electrical and Computer Engineering

Granting Institution

Ryerson University

LAC Thesis Type

Thesis