2015 7th International Conference on Computational Intelligence, Communication Systems and Networks 2015
DOI: 10.1109/cicsyn.2015.34
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Key Frame Extraction and Foreground Modelling Using K-Means Clustering

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Cited by 11 publications
(6 citation statements)
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“…The initial phase involves preprocessing, commencing with transforming input films into a series of frames. Next, the keyframe selection method is applied to video frames using the Cosine Similarity (CS) algorithm [25] by measuring the similarity between two frames (current frame and prior keyframe). Next, compare the acquired result with the similarity threshold value to ascertain if the frame qualifies as a keyframe.…”
Section: Proposed Offline Methods To Generate Anomaly Detection Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…The initial phase involves preprocessing, commencing with transforming input films into a series of frames. Next, the keyframe selection method is applied to video frames using the Cosine Similarity (CS) algorithm [25] by measuring the similarity between two frames (current frame and prior keyframe). Next, compare the acquired result with the similarity threshold value to ascertain if the frame qualifies as a keyframe.…”
Section: Proposed Offline Methods To Generate Anomaly Detection Modelmentioning
confidence: 99%
“…Keyframes are frames in a video that provide a comprehensive summary of the entire video and can be extracted to remove nearby repetitive frames effectively. Keyframe selection is the process of choosing frames that include new information [25]. The keyframe selection process aims to summarize the video by eliminating redundant adjacent frames to decrease the amount of information to be processed and reduce computational complexity [26].…”
Section: A Pre-processing Stagementioning
confidence: 99%
“…In this method colour feature information is employed, shots are clustered into sub-shots, and the frame that has the largest entropy is selected as a KF from each class. In [30] presented a method for extracting KFs and isolating the foreground. They employed a k-means algorithm along with means-squared error.…”
Section: : Global Comparison Between Framesmentioning
confidence: 99%
“…The set of key frames is created with frames that have the closest distance from the center of the cluster. In [21,22] fuzzy K-means-and fuzzy C-means-based methods for the key frame selection are presented. The clusters are generated based on the different features like motion sequences and the distance matrix score.…”
Section: Cluster-based Key Frame Extractionmentioning
confidence: 99%