Video key frame extraction through dynamic Delaunay clustering with a structural constraint

• Published in: Journal of visual communication and image representation Vol. 24; no. 7; pp. 1212 - 1227
• Main Authors: Kuanar, Sanjay K., Panda, Rameswar, Chowdhury, Ananda S.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.10.2013; Elsevier
• Subjects: Applied sciences; Artificial intelligence; Clustering; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Data processing. List processing. Character string processing; Delaunay graphs; Deviation ratio; Edge pruning; Exact sciences and technology; Feature extraction; Information retrieval. Graph; Information-theoretic pre-sampling; Key frame visualization; Memory organisation. Data processing; Pattern recognition. Digital image processing. Computational geometry; Software; Theoretical computing; Video summarization; Delaunay graphs; Edge pruning; Key frame visualization; Deviation ratio; Feature extraction; Video summarization; Clustering; Information-theoretic pre-sampling; Visualization; Video signal; Iterative method; Successive frame; Video databases; Graph connectivity; Selection criterion; Pruning(tree); Sampling; key frame; Pattern extraction; Multimedia; Lower bound; Computer vision; Abstract; Cluster; Social network; Delaunay triangulation; Information browsing; Web site; Mutual information; Information theory
• ISSN: 1047-3203; 1095-9076
• DOI: 10.1016/j.jvcir.2013.08.003

Key frame based video summarization has emerged as an important area of research for the multimedia community. Video key frames enable an user to access any video in a friendly and meaningful way. In this paper, we propose an automated method of video key frame extraction using dynamic Delaunay graph clustering via an iterative edge pruning strategy. A structural constraint in form of a lower limit on the deviation ratio of the graph vertices further improves the video summary. We also employ an information-theoretic pre-sampling where significant valleys in the mutual information profile of the successive frames in a video are used to capture more informative frames. Various video key frame visualization techniques for efficient video browsing and navigation purposes are incorporated. A comprehensive evaluation on 100 videos from the Open Video and YouTube databases using both objective and subjective measures demonstrate the superiority of our key frame extraction method.