2020
DOI: 10.1109/access.2020.3040861
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Video Shot Boundary Detection Based on Feature Fusion and Clustering Technique

Abstract: For the problems of low accuracy and high complexity in detection of gradual shot boundary and long shot, a new video shot boundary detection algorithm based on feature fusion and clustering technique (FFCT) is proposed. In the algorithm, the interval frames of video sequence are selected, converted to gray images and scaled by sampling. With the frames, the speed-up robust features (SURF) and fingerprint features are extracted from non-compressed domain and compressed domain, and then the extracted features a… Show more

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Cited by 10 publications
(6 citation statements)
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“…K-mean clustering-based classification technique was proposed in [61]. K-mean Clustering and linear discriminant analysis (LDA) using SURF and DCT fingerprint features were proposed in [40]. Some of the well-trained CNNs were utilized for low-level and high-level feature extraction in [62] and [63].…”
Section: B Scene Transition Pattern Feature-based Approachmentioning
confidence: 99%
See 2 more Smart Citations
“…K-mean clustering-based classification technique was proposed in [61]. K-mean Clustering and linear discriminant analysis (LDA) using SURF and DCT fingerprint features were proposed in [40]. Some of the well-trained CNNs were utilized for low-level and high-level feature extraction in [62] and [63].…”
Section: B Scene Transition Pattern Feature-based Approachmentioning
confidence: 99%
“…The HSI-CNN [12] method achieved a 100% recall rate for both the "Zoom-in" and "Zoom-out" motion, whereas our method achieved lower accuracy. In Table 17, we compare with the feature fusion and K-means clusteringbased (FFCT) method [40] for gradual transition detection on video datasets with low and high dimensional frames. It is observed that our proposed SOCMR method achieved up to 4.45% and 7.29% higher F-1 rates for videos with lower (≤ 352 × 288) and higher (≥ 720 × 1280) frame dimensions, respectively.…”
Section: Camera Motion Object Motionmentioning
confidence: 99%
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“…The characteristic merging and segmentation approach algorithm that is discussed in this paper by Feng-Feng Duan et al [11] takes into consideration both the global and indeed the local variables of the movie interval images. It doesn't just recover the characteristics of the condensed region, but additionally recovers the characteristics of the non-compressed zone, which enables it to perform a retrieval and merging of the characteristics that is exhaustive as well as precise.…”
Section: Related Workmentioning
confidence: 99%
“…Duan et al 16 introduced an SBD system based on feature fusion and clustering technology (FFCT). Sampling process have been selected, converted and scaled the interval frames of the video sequence to detect transitions.…”
Section: Related Workmentioning
confidence: 99%