A Formal Study of Shot Boundary Detection

This paper conducts a formal study of the shot boundary detection problem. First, a general formal framework of shot boundary detection techniques is proposed. Three critical techniques, i.e., the representation of visual content, the construction of continuity signal and the classification of continuity values, are identified and formulated in the perspective of pattern recognition. Meanwhile, the major challenges to the framework are identified. Second, a comprehensive review of the existing approaches is conducted. The representative approaches are categorized and compared according to their roles in the formal framework. Based on the comparison of the existing approaches, optimal criteria for each module of the framework are discussed, which will provide practical guide for developing novel methods. Third, with all the above issues considered, we present a unified shot boundary detection system based on graph partition model. Extensive experiments are carried out on the platform of TRECVID. The experiments not only verify the optimal criteria discussed above, but also show that the proposed approach is among the best in the evaluation of TRECVID 2005. Finally, we conclude the paper and present some further discussions on what shot boundary detection can learn from other related fields

[1]  J. Canny Finding Edges and Lines in Images , 1983 .

[2]  Kikukawa Takeshi,et al.  Development of an Automatic Summary Editing System for the Audio Visual Resources. , 1992 .

[3]  Adnan M. Alattar Detecting and compressing dissolve regions in video sequences with a DVI multimedia image compression algorithm , 1993, 1993 IEEE International Symposium on Circuits and Systems.

[4]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .

[5]  Ramesh C. Jain,et al.  Digital video segmentation , 1994, MULTIMEDIA '94.

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

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

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

[9]  Wolfgang Effelsberg,et al.  Video abstracting , 1997, CACM.

[10]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Ramin Zabih,et al.  Comparing images using color coherence vectors , 1997, MULTIMEDIA '96.

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

[13]  Rainer Lienhart,et al.  Comparison of automatic shot boundary detection algorithms , 1998, Electronic Imaging.

[14]  J. C. BurgesChristopher A Tutorial on Support Vector Machines for Pattern Recognition , 1998 .

[15]  A. Murat Tekalp,et al.  A high-performance shot boundary detection algorithm using multiple cues , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

[16]  David S. Doermann,et al.  Special-effect edit detection using VideoTrails: a comparison with existing techniques , 1998, Electronic Imaging.

[17]  Patrick Bouthemy,et al.  A unified approach to shot change detection and camera motion characterization , 1999, IEEE Trans. Circuits Syst. Video Technol..

[18]  Lei Zhang,et al.  A CBIR method based on color-spatial feature , 1999, Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030).

[19]  Mohan S. Kankanhalli,et al.  Temporal multiresolution analysis for video segmentation , 1999, Electronic Imaging.

[20]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

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

[22]  Greg Schohn,et al.  Less is More: Active Learning with Support Vector Machines , 2000, ICML.

[23]  Ba Tu Truong,et al.  New enhancements to cut, fade, and dissolve detection processes in video segmentation , 2000, ACM Multimedia.

[24]  Min Gyo Chung,et al.  A scene boundary detection method , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[25]  Nuno Vasconcelos,et al.  Statistical models of video structure for content analysis and characterization , 2000, IEEE Trans. Image Process..

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

[27]  Malcolm Slaney,et al.  Multimedia edges: finding hierarchy in all dimensions , 2001, MULTIMEDIA '01.

[28]  Chris H. Q. Ding,et al.  A min-max cut algorithm for graph partitioning and data clustering , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[29]  B. S. Manjunath,et al.  Unsupervised Segmentation of Color-Texture Regions in Images and Video , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  Chong-Wah Ngo,et al.  Video partitioning by temporal slice coherency , 2001, IEEE Trans. Circuits Syst. Video Technol..

[31]  Rainer Lienhart,et al.  Reliable dissolve detection , 2001, IS&T/SPIE Electronic Imaging.

[32]  Sung-Han Park,et al.  An Automatic Cut Detection Algorithm Using Median Filter And Neural Network , 2002 .

[33]  David R. Bull,et al.  Video Retrieval Using Global Features in Keyframes , 2002, TREC.

[34]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[35]  Mikolaj Leszczuk,et al.  Accuracy vs. Speed Trade-Off in Detecting of Shots in Video Content for Abstracting Digital Video Libraries , 2002, IDMS/PROMS.

[36]  Eamonn J. Keogh,et al.  Segmenting Time Series: A Survey and Novel Approach , 2002 .

[37]  Alan Hanjalic,et al.  Shot-boundary detection: unraveled and resolved? , 2002, IEEE Trans. Circuits Syst. Video Technol..

[38]  Avideh Zakhor,et al.  Applications of Video-Content Analysis and Retrieval , 2002, IEEE Multim..

[39]  Thierry Pun,et al.  Information-Theoretic Framework for The Joint Temporal Partionning and Representation of Video Data , 2003 .

[40]  Nicole Vincent,et al.  A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval , 2003, Real Time Imaging.

[41]  Harriet J. Nock,et al.  Discriminative model fusion for semantic concept detection and annotation in video , 2003, ACM Multimedia.

[42]  Chong-Wah Ngo,et al.  A robust dissolve detector by support vector machine , 2003, ACM Multimedia.

[43]  Tat-Seng Chua,et al.  An unified framework for shot boundary detection via active learning , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[44]  King Ngi Ngan,et al.  High accuracy flashlight scene determination for shot boundary detection , 2003, Signal Process. Image Commun..

[45]  Jeffrey Mark Siskind,et al.  Image Segmentation with Ratio Cut , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[46]  Arnaldo de Albuquerque Araújo,et al.  Video segmentation based on 2D image analysis , 2003, Pattern Recognit. Lett..

[47]  Yanjun Qi,et al.  Supervised classification for video shot segmentation , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[48]  Angelo Chianese,et al.  A Formal Model for Video Shot Segmentation and its Application via Animate Vision , 2004, Multimedia Tools and Applications.

[49]  Hugh E. Williams,et al.  RMIT University at TRECVID 2004 , 2004, TRECVID.

[50]  Daniel P. Huttenlocher,et al.  Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.

[51]  Matthew Cooper Video segmentation combining similarity analysis and classification , 2004, MULTIMEDIA '04.

[52]  Jing Xiao,et al.  Content-Based Video Indexing and Retrieval , 2004 .

[53]  Alan Hanjalic,et al.  TU Delft at TRECVID 2005: Shot Boundary Detection , 2005, TRECVID.

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

[55]  Cees G. M. Snoek,et al.  Early versus late fusion in semantic video analysis , 2005, MULTIMEDIA '05.

[56]  Stephen W. Smoliar,et al.  Video parsing and browsing using compressed data , 1995, Multimedia Tools and Applications.

[57]  Tsinghua University at TRECVID 2005 , 2005, TRECVID.

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

[59]  Ramesh C. Jain,et al.  ACM SIGMM retreat report on future directions in multimedia research , 2005, TOMCCAP.

[60]  Bo Zhang,et al.  Graph Partition Model for Robust Temporal Data Segmentation , 2005, PAKDD.

[61]  José Manuel Menéndez,et al.  A unified model for techniques on video-shot transition detection , 2005, IEEE Transactions on Multimedia.

[62]  Bo Zhang,et al.  A unified shot boundary detection framework based on graph partition model , 2005, MULTIMEDIA '05.

[63]  Sen Liu,et al.  A new general framework for shot boundary detection and key-frame extraction , 2005, MIR '05.

[64]  Chih-Jen Lin,et al.  A Practical Guide to Support Vector Classication , 2008 .