Fuzzy Logic Methods for Video Shot Boundary Detection and Classification

A fuzzy logic system for the detection and classification of shot boundaries in uncompressed video sequences is presented. It integrates multiple sources of information and knowledge of editing procedures to detect shot boundaries. Furthermore, the system classifies the editing process employed to create the shot boundary into one of the following categories: abrupt cut, fade-in, fade-out, or dissolve. This system was tested on a database containing a wide variety of video classes. It achieved combined recall and precision rates that significantly exceed those of existing threshold-based techniques, and it correctly classified a high percentage of the detected boundaries.

[1]  Ullas Gargi,et al.  Evaluation of video sequence indexing and hierarchical video indexing , 1995, Electronic Imaging.

[2]  Atreyi Kankanhalli,et al.  Automatic partitioning of full-motion video , 1993, Multimedia Systems.

[3]  Ralph M. Ford,et al.  Metrics for shot boundary detection in digital video sequences , 2000, Multimedia Systems.

[4]  Yap-Peng Tan,et al.  Modified Kolmogorov-Smirnov metric for shot boundary detection , 2003 .

[5]  Akio Nagasaka,et al.  Automatic Video Indexing and Full-Video Search for Object Appearances , 1991, VDB.

[6]  Arding Hsu,et al.  Image processing on compressed data for large video databases , 1993, MULTIMEDIA '93.

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

[8]  Harry L. Van Trees,et al.  Detection, Estimation, and Modulation Theory, Part I , 1968 .

[9]  H. V. Trees.  Detection, Estimation, And Modulation Theory , 2001 .

[10]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[11]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[12]  Ramin Zabih,et al.  A feature-based algorithm for detecting and classifying production effects , 1999, Multimedia Systems.

[13]  Ramesh C. Jain,et al.  Production model based digital video segmentation , 1995, Multimedia Tools and Applications.

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

[15]  Kanad K. Biswas,et al.  A fuzzy theoretic approach for video segmentation using syntactic features , 2001, Pattern Recognit. Lett..

[16]  J. Mendel.  Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

[17]  Boon-Lock Yeo,et al.  Rapid scene analysis on compressed video , 1995, IEEE Trans. Circuits Syst. Video Technol..

[18]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[19]  Nilesh V. Patel,et al.  Statistical approach to scene change detection , 1995, Electronic Imaging.

[20]  Wei Jyh Heng.  Shot boundary refinement for long transition in digital video sequence , 2002, IEEE Trans. Multim..

[21]  Rangachar Kasturi,et al.  Machine vision , 1995 .

[22]  F. Martin McNeill,et al.  Fuzzy Logic: A Practical Approach , 1994 .

[23]  John S. Boreczky,et al.  Comparison of video shot boundary detection techniques , 1996, J. Electronic Imaging.

[24]  Ralph M. Ford.  Fuzzy logic approach to digital video segmentation , 1997, Electronic Imaging.

[25]  Akio Yoneyama,et al.  Universal scene change detection on MPEG-coded data domain , 1997, Electronic Imaging.

[26]  Glorianna Davenport,et al.  Cinematic primitives for multimedia , 1991, IEEE Computer Graphics and Applications.