Fractal based video shot cut/fade detection and classification

Authors:
Zeinab Zeinalpour-Tabrizi;Amir Farid Aminian-Modarres;Mahmood Fathy;Mohammad Reza Jahed-Motlagh
Affiliations:
Computer Engineering Faculty, Iran University of Science and Technology, Tehran, Iran;Sadjad Institute of Higher Education, Mashhad, Iran;Computer Engineering Faculty, Iran University of Science and Technology, Tehran, Iran;Computer Engineering Faculty, Iran University of Science and Technology, Tehran, Iran
Venue:
AMT'10 Proceedings of the 6th international conference on Active media technology
Year:
2010

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Abstract

Video segmentation plays an important role in video indexing, content-based video coding and retrieval. In this paper, we propose a new method for cut and fade detection using fractal dimension. We also classify frames into three categories: "CUT", "FADE IN/OUT", and "None SHOT". To test our method, we used 20 videos which contain more than 33,000 frames in different subjects, including different type of shot boundaries. It was also successfully compared to two other methods of shot boundary detection. Results from experiments depict the improved precision and recall of the proposed method in recognition of the fade in/out frames our database.