Video Structure Analysis: A survey
DOI:
https://doi.org/10.29304/jqcsm.2023.15.21304Keywords:
Video Structure Analysis (VSA), Scenes Detection (SD), Shot Boundary Detection (SBD), Cut Transition (CT), Gradual Transition (GT), Feature Extraction (FE)Abstract
Due to the great and rapid development in the electronic field, the spread of the Internet, and the diversity of social media, the spread and transmission of data have become an important matter in different areas of life. The video is one of the most important of this information, which includes a lot of information that requires storing and retrieving a large database. Therefore, video structure analysis is the basis for facilitating the video search process based on its contents, indexing, and retrieval. In this research, we will present a survey of the video structure analysis process, the basic concepts and all related processing steps, the procedures used in each method, and the most prominent works used in each step.
Downloads
References
B. A. Halim, T. Faiza, and H. Seridi, “Shot Boundary Detection: Fundamental Concepts and Survey.,” in CITSC, 2019, pp. 34–40.
I. H. Ali and T. T. Al-Fatlawi, “Key Frame Extraction Methods,” International Journal of Pure and Applied Mathematics, vol. 119, no. 10, pp. 485–490, 2018.
S. H. Abdulhussain, A. R. Ramli, M. I. Saripan, B. M. Mahmmod, S. A. R. Al-Haddad, and W. A. Jassim, “Methods and challenges in shot boundary detection: a review,” Entropy, vol. 20, no. 4, p. 214, 2018.
Z. M. Lu and Y. Shi, “Fast video shot boundary detection based on SVD and pattern matching,” IEEE Transactions on Image Processing, vol. 22, no. 12, pp. 5136–5145, 2013, doi: 10.1109/TIP.2013.2282081.
M. Del Fabro and L. Böszörmenyi, “State-of-the-art and future challenges in video scene detection: a survey,” Multimedia Systems, vol. 19, no. 5, pp. 427–454, 2013, doi: 10.1007/s00530-013-0306-4.
J. Varghese and K. N. Nair, “Detecting Video Shot Boundaries by Modified Tomography,” in Proceedings of the Third International Symposium on Computer Vision and the Internet, 2016, pp. 131–135.
J. Son, S. Lee, S. Park, and S. Kim, “Video scene segmentation based on multiview shot representation,” in 2016 International Conference on Information and Communication Technology Convergence (ICTC), 2016, pp. 381–383, doi: 10.1109/ICTC.2016.7763501.
G. Gao and C. H. Liu, “Multimodality Movie Scene Detection,” in Video Cataloguing Structure Parsing and Content Extraction, Boca Raton, FL, USA.: CRC Press,Inc., 2015, pp. 49–60.
H. Sundaram and S.-F. Chang, “Computable scenes and structures in films,” IEEE Transactions on Multimedia, vol. 4, no. 4, pp. 482–491, 2002, doi: 10.1109/TMM.2002.802017.
W. Hu, N. Xie, L. Li, X. Zeng, and S. Maybank, “A survey on visual content-based video indexing and retrieval,” IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, vol. 41, no. 6. pp. 797–819, 2011, doi: 10.1109/TSMCC.2011.2109710.
J. Yuan et al., “A formal study of shot boundary detection,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 2, pp. 168–186, 2007, doi: 10.1109/TCSVT.2006.888023.
H. Sundaram and S.-F. Chang, “Video scene segmentation using video and audio features,” in 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532), 2000, vol. 2, pp. 1145–1148, doi: 10.1109/ICME.2000.871563.
L. Zhao, W. Qi, Y.-J. Wang, S.-Q. Yang, and H. Zhang, “Video shot grouping using best-first model merging,” in Storage and Retrieval for Media Databases 2001, 2001, vol. 4315, pp. 262–270.
Z. Rasheed and M. Shah, “Scene detection in Hollywood movies and TV shows,” in 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003, vol. 2, pp. II–343, doi: 10.1109/CVPR.2003.1211489.
W. Tavanapong and J. Zhou, “Shot clustering techniques for story browsing,” IEEE Transactions on Multimedia, vol. 6, no. 4, pp. 517–527, 2004, doi: 10.1109/TMM.2004.830810.
Z. Rasheed and M. Shah, “Detection and representation of scenes in videos,” IEEE Transactions on Multimedia, vol. 7, no. 6, pp. 1097–1105, 2005, doi: 10.1109/TMM.2005.858392.
Y.-P. Tan and H. Lu, “Model-based clustering and analysis of video scenes,” in Proceedings. International Conference on Image Processing, 2002, vol. 1, pp. I–I, doi: 10.1109/ICIP.2002.1038099.
Y. Zhai and M. Shah, “Video scene segmentation using Markov chain Monte Carlo,” IEEE Transactions on Multimedia, vol. 8, no. 4, pp. 686–697, 2006, doi: 10.1109/TMM.2006.876299.
Z. Gu, T. Mei, X. Hua, X. Wu, and S. Li, “EMS: Energy Minimization Based Video Scene Segmentation,” in 2007 IEEE International Conference on Multimedia and Expo, 2007, pp. 520–523, doi: 10.1109/ICME.2007.4284701.
N. Goela, K. Wilson, F. Niu, A. Divakaran, and I. Otsuka, “An SVM Framework for Genre-Independent Scene Change Detection,” in 2007 IEEE International Conference on Multimedia and Expo, 2007, pp. 532–535, doi: 10.1109/ICME.2007.4284704.
Z. Wu and P. Xu, “Shot boundary detection in video retrieval,” in 2013 IEEE 4th International Conference on Electronics Information and Emergency Communication, 2013, pp. 86–89, doi: 10.1109/ICEIEC.2013.6835460.
G. Gao and C. H. Liu, Video Cataloguing: Structure Parsing and Content Extraction. Boca Raton, FL, USA.: CRC Press,Inc., 2015.
I. H. Ali and T. T. Al-Fatlawi, “Video’s Cut Transitions Detection Based on Multiple Features,” Journal of Computational and Theoretical Nanoscience, vol. 16, no. 3, pp. 1203–1211, 2019.
Y. N. Li, Z. M. Lu, and X. M. Niu, “Fast video shot boundary detection framework employing pre-processing techniques,” IET Image Processing, vol. 3, no. 3, pp. 121–134, 2009, doi: 10.1049/iet-ipr.2007.0193.
S. D. Thepade and A. A. Tonge, “Extraction of key frames from video using discrete cosine transform,” in 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies, ICCICCT 2014, 2014, pp. 1294–1297, doi: 10.1109/ICCICCT.2014.6993160.
A. Divakaran, R. Radhakrishnan, and K. A. Peker, “Motion activity-based extraction of key-frames from video shots,” in Proceedings. International Conference on Image Processing, 2002, vol. 1, pp. I–I, doi: 10.1109/ICIP.2002.1038180.
T. Liu, X. Zhang, J. Feng, and K. T. Lo, “Shot reconstruction degree: A novel criterion for key frame selection,” Pattern Recognition Letters, vol. 25, no. 12, pp. 1451–1457, 2004, doi: 10.1016/j.patrec.2004.05.020.
S. V. Porter, M. Mirmehdi, and B. T. Thomas, “A shortest path representation for video summarisation,” in Proceedings - 12th International Conference on Image Analysis and Processing, ICIAP 2003, 2003, pp. 460–465, doi: 10.1109/ICIAP.2003.1234093.
Rong Pan, Yumin Tian, and Zhong Wang, “Key-frame extraction based on clustering,” in 2010 IEEE International Conference on Progress in Informatics and Computing, 2010, vol. 2, pp. 867–871, doi: 10.1109/PIC.2010.5687901.
A. Nasreen, K. Roy, K. Roy, and G. Shobha, “Key Frame Extraction and Foreground Modelling Using K-Means Clustering,” in Proceedings - 7th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2015, 2015, pp. 141–145, doi: 10.1109/CICSyN.2015.34.
B. Ghanem, T. Zhang, and A. Narendra, “Robust video registration applied to field-sports video analysis,” Computer Engineering, pp. 1473–1476, 2012.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Talib T. Al-Fatlawi, Rafeef M.hamza , Adil L. Albukhnefis
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
