2016
DOI: 10.1016/j.procs.2016.06.075
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Video Summary Based on F-Sift, Tamura Textural and Middle Level Semantic Feature

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Cited by 10 publications
(3 citation statements)
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“…At present, the common key frame extraction methods mainly include the key frame extraction algorithm [4,5] based on SIFT features, the clustering-based key frame extraction algorithm [6,7], and [8], a key frame extraction algorithm based on motion analysis, however, in the key frame extraction algorithm based on SIFT features in the video key frame extraction. The smooth edge targets cannot accurately extract the feature points and have poor real-time performance, thus affecting the integrity and effectiveness of the key frame extraction [9,10]. Clusteringbased key frame extraction algorithm generally needs to set the center and number of clusters in advance in the clustering process.…”
Section: The Dance Teaching Methods Based On Aimentioning
confidence: 99%
“…At present, the common key frame extraction methods mainly include the key frame extraction algorithm [4,5] based on SIFT features, the clustering-based key frame extraction algorithm [6,7], and [8], a key frame extraction algorithm based on motion analysis, however, in the key frame extraction algorithm based on SIFT features in the video key frame extraction. The smooth edge targets cannot accurately extract the feature points and have poor real-time performance, thus affecting the integrity and effectiveness of the key frame extraction [9,10]. Clusteringbased key frame extraction algorithm generally needs to set the center and number of clusters in advance in the clustering process.…”
Section: The Dance Teaching Methods Based On Aimentioning
confidence: 99%
“…In [6], to reduce the computations, SIFT is extracted from selected candidate keyframes. SIFT features are computed for all the candidate frames to find points of interest (POI).…”
Section: Related Workmentioning
confidence: 99%
“…The energy equals to the square root of ASM, as (10). It is often used in fingerprint recognition [38] and plant classification [39] .…”
Section: Orderliness Patterns Of Glcmmentioning
confidence: 99%