International Journal of Computer Vision
Video summarization by curve simplification
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Dynamic selection and effective compression of key frames for video abstraction
Pattern Recognition Letters
Keyframe-based video summarization using Delaunay clustering
International Journal on Digital Libraries
Video abstraction: A systematic review and classification
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Video summarisation: A conceptual framework and survey of the state of the art
Journal of Visual Communication and Image Representation
k-means requires exponentially many iterations even in the plane
Proceedings of the twenty-fifth annual symposium on Computational geometry
IEEE Transactions on Circuits and Systems for Video Technology
Moments and Moment Invariants in Pattern Recognition
Moments and Moment Invariants in Pattern Recognition
STIMO: STIll and MOving video storyboard for the web scenario
Multimedia Tools and Applications
Toward a conceptual framework of key-frame extraction and storyboard display for video summarization
Journal of the American Society for Information Science and Technology
Performance evaluation of an intelligent video surveillance system - A case study
Computer Vision and Image Understanding
VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method
Pattern Recognition Letters
Video visualization for compact presentation and fast browsing of pictorial content
IEEE Transactions on Circuits and Systems for Video Technology
Efficient summarization of stereoscopic video sequences
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Multimedia
Efficient visual attention based framework for extracting key frames from videos
Image Communication
Surveillance video synopsis in the compressed domain for fast video browsing
Journal of Visual Communication and Image Representation
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Video summarization is a method to reduce redundancy and generate succinct representation of the video data. One of the mechanisms to generate video summaries is to extract key frames which represent the most important content of the video. In this paper, a new technique for key frame extraction is presented. The scheme uses an aggregation mechanism to combine the visual features extracted from the correlation of RGB color channels, color histogram, and moments of inertia to extract key frames from the video. An adaptive formula is then used to combine the results of the current iteration with those from the previous. The use of the adaptive formula generates a smooth output function and also reduces redundancy. The results are compared to some of the other techniques based on objective criteria. The experimental results show that the proposed technique generates summaries that are closer to the summaries created by humans.