Multiresolution median filtering based video temporal segmentation

In this paper we introduce an enhanced graph partition model, more robust, used for video sequences temporal segmentation. In the first part we examine the formal framework of the shot boundary detection techniques implemented in the recent years, emphasizing the weakness and strength for each method. In the second phase we present our novel algorithm that applies a scale space median filtering on a min-max objective function that optimize the association within each graph cut in order to remove noise caused by camera movement or large object displacement. The algorithm evaluation is done on a subset of movies from the TRECVID 2001 and 2002 video database which demonstrate the improved performance of our method regardless to the noise gender, with precision and recall rates of average 90% and 86 %, respectively. In the end we conclude the paper and present some further implementation.

[1]  Rainer Lienhart,et al.  Reliable Transition Detection in Videos: A Survey and Practitioner's Guide , 2001, Int. J. Image Graph..

[2]  Ramin Zabih,et al.  A feature-based algorithm for detecting and classifying scene breaks , 1995, MULTIMEDIA '95.

[3]  Majid Mirmehdi,et al.  Video cut detection using frequency domain correlation , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[4]  Soo-Chang Pei,et al.  Efficient and effective wipe detection in MPEG compressed video based on the macroblock information , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[5]  Suresh K. Choubey Generic and fully automatic content-based image retrieval using color , 1997, Pattern Recognit. Lett..

[6]  Janko Calic,et al.  Temporal Segmentation of MPEG Video Streams , 2002, EURASIP J. Adv. Signal Process..

[7]  Ullas Gargi,et al.  Performance characterization of video-shot-change detection methods , 2000, IEEE Trans. Circuits Syst. Video Technol..

[8]  Bo Zhang,et al.  A novel shot boundary detection framework , 2005, Visual Communications and Image Processing.

[9]  Bo Zhang,et al.  A Formal Study of Shot Boundary Detection , 2007, IEEE Transactions on Circuits and Systems for Video Technology.