Item
Ministerio de Econom铆a y Competitividad (Espanya)
Generalitat de Catalunya. Ag猫ncia de Gesti贸 d鈥橝juts Universitaris i de Recerca |
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Guo, Yuejun
Xu, Qing Sun, Shihua Luo, Xiaoxiao Sbert, Mateu |
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This paper studies the relative entropy and its square root as distance measures of
neighboring video frames for video key frame extraction. We develop a novel approach handling
both common and wavelet video sequences, in which the extreme Studentized deviate test is
exploited to identify shot boundaries for segmenting a video sequence into shots. Then, video shots
can be divided into different sub-shots, according to whether the video content change is large or
not, and key frames are extracted from sub-shots. The proposed technique is general, effective and
efficient to deal with video sequences of any kind. Our new approach can offer optional additional
multiscale summarizations of video data, achieving a balance between having more details and
maintaining less redundancy. Extensive experimental results show that the new scheme obtains
very encouraging results in video key frame extraction, in terms of both objective evaluation metrics
and subjective visual perception This work has been funded by the Natural Science Foundation of China (61471261, 61179067, U1333110) and by Grants TIN2013-47276-C6-1-R from the Spanish Government and 2014-SGR-1232 from the Catalan Government (Spain) |
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http://hdl.handle.net/2072/298448 | |
eng | |
MDPI (Multidisciplinary Digital Publishing Institute) | |
Attribution 4.0 Spain | |
http://creativecommons.org/licenses/by/4.0/es/ | |
Imatge -- Segmentaci贸
Imaging segmentation |
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Selecting Video Key Frames Based on Relative Entropy and the Extreme Studentized Deviate Test | |
info:eu-repo/semantics/article | |
Recercat |