Nowadays, huge amount of multimedia repositories
make the browsing, retrieval and delivery of video contents very slow
and even difficult tasks. Video summarization has been proposed to
improve faster browsing of large video collections and more efficient
content indexing and access. In this paper, we focus on approaches to
video summarization. The video summaries can be generated in many
different forms. However, two fundamentals ways to generate
summaries are static and dynamic. We present different techniques
for each mode in the literature and describe some features used for
generating video summaries. We conclude with perspective for
further research.
[1] B. T. Truong and S. Venkatesh, “Video Abstraction: A Systematic
Review and Classification,” ACM Transactions on Multimedia
Computing, Communications, and Applications (TOMM), vol. 3, no. 3,
February 2007.
[2] E. Asadi and N. M. Charkari, “Video Summarization Using Fuzzy CMeans
Clustering,” in 20th Iranian Conference on Electrical
Engineering, (ICEE2012). IEEE, 15-17 May 2012, pp. 690 – 694.
[3] Z. Xiong, R. Radhakrishnan, A. Divakaran, Y. Rui, and T. S. Huang, A
Unified Framework for Video Summarization, Browsing Retrieval: with
Applications to Consumer and Surveillance Video. Academic
Press.2006.
[4] T. Mei, L.-X. Tang, J. Tang, and X.-S. Hua, “Near-Lossless Semantic
Video Summarization and Its Applications to Video Analysis,” ACM
Trans. Multimedia Computing Communications and Applications, June
2013.
[5] E. J. Y. C. Cahuina and G. C. Chavez, “A New Method for Static Video
Summarization Using Local Descriptors and Video Temporal
Segmentation,” in 26th Conference on Graphics, Patterns and Images
(SIBGRAPI). IEEE, 5-8 Aug 2013, pp. 226–233.
[6] E. Mendi, H. B. Clemente, and C. Bayrak, “Sports video summarization
based on motion analysis,” Computers and Electrical Engineering, vol.
39, pp. 790–796, April 2013.
[7] E. Mendi and C. Bayrak, “Shot Boundary Detection and Key Frame
Extraction using Salient Region Detection and Structural Similarity,” in
ACM SE ’10 Proceedings of the 48th Annual Southeast Regional
Conference, no. 66, 2010.
[8] E. J. Y. Cayllahua-Cahuina, G. Camara-Chavez, and D. Menotti, “A
static video summarization approach with automatic shot detection using
color histograms,” 2012.
[9] M. K.M., G. N.M., and I. M.A., “VGRAPH: An Effective Approach for
Generating Static Video Summaries,” in IEEE International Conference
on Computer Vision Workshops (ICCVW). IEEE, 2-8 Dec 2013, pp.
811 – 818.
[10] J. Li, “Video Shot Segmentation and Key Frame Extraction Based on
SIFT Feature,” in 2012 International Conference on Image Analysis and
Signal Processing (IASP). IEEE, 9-11 Nov 2012, pp. 1–8.
[11] L. D.G., “Object Recognition from Local Scale-Invariant Features,” in
The Proceedings of the Seventh IEEE International Conference on
Computer Vision, 1999, vol. 2. IEEE, 20-27 Sep 1999, pp. 1150–1157.
[12] Y. Tabii and R. O. H. Thami, “A new method for soccer video
summarization based on shot detection, classification and finite state
machine,” in SETIT 2009 5th International Conference: Sciences of
Electronic, Technologies of Information and Telecommunications, 22-26
March 2009.
[13] X. Sun and M. S. Kankanhalli, “Video Summarization Using RSequences,”
Real-Time Imaging, vol. 6, pp. 449–459, December 2000.
[14] J. Hou, J. Kang, and N. Qi, On Vocabulary Size in Bag-of-Visual-
Words Representation, ser. Lecture Notes in Computer Science, 21-24
September 2010, vol. 6297, pp. 414–424.
[15] Z. Yuan, T. Lu, D. Wu, and H. Y. Yu Huang, “Video Summarization
with Semantic Concept Preservation,” in MUM ’11 Proceedings of the
10th International Conference on Mobile and Ubiquitous Multimedia,
2011, pp. 109–112.
[16] V. N. and L. A., “Bayesian Modeling of Video Editing and Structure:
Semantic features for Video Summarization and Browsing,” in
Proceedings of 1998 International Conference on Image Processing.
ICIP 98, vol. 3. IEEE, 4-7 Oct 1998, pp. 153–157. [17] Cvetkovic, S. Jelenkovic, and S. V. M. Nikolic, “Video summarization
using color features and efficient adaptive threshold technique,”
Przeglad Elektrotechniczny, vol. R. 89, nr 2a, pp. 247 – 250, 2013.
[18] N. Ejaza, T. B. Tariqb, and S. W. Baika, “Adaptive key frame extraction
for video summarization using an aggregation mechanism,” Journal of
Visual Communication and Image Representation, vol. 23, no. 7,
pp.1031–1040, October 2012.
[19] M. Sophie, G. Mick¨ael, and P. Denis, “Résumé de vidéo à partir d’un
modèle d’attention visuelle,” in GRETSI - Actes de Colloque, G.
d’Etudes du Traitement du Signal et des Images, Ed., 2007.
[20] M. S. Lew, N. Sebe, C. Djeraba, and R. Jain, “Content-Based
Multimedia Information Retrieval: State of the Art and Challenges,”
ACM Transactions on Multimedia Computing, Communications, and
Applications (TOMM), vol. 2, pp. 1–9, February 2006.
[21] Y.-F. Ma and H.-J. Zhang, “A model of motion attention for video
skimming,” in Proceedings. International Conference on Image
Processing, vol. 1. IEEE, 2002, pp. 129–132.
[22] S. Zhu, Z. Liang, and Y. Liu, Automatic Video Abstraction via the
Progress of Story, ser. Lecture Notes in Computer Science. Springer
Berlin Heidelberg, 2010, vol. 6297, pp. 308–318.
[23] R. Laganière, R. Bacco, A. Hocevar, P. Lambert, G. Païs, and B. E.
Ionescu, “Video summarization from spatio-temporal features,” in
TVS’08 Proceedings of the 2nd ACM TRECVid Video Summarization
Workshop, 2008, pp. 144–148.
[24] Y. Gao, W.-B. Wang, J.-H. Yong and H.-J. Gu, “Dynamic video
summarization using two-level redundancy detection,” Multimedia
Tools and Applications, vol. 42, pp. 233–250, April 2009.
[25] M. G. Brown, J. T. Foote, G. J. F. Jones, K. S. Jones, and S. J. Young,
“Automatic content-based retrieval of broadcast news,” in
MULTIMEDIA ’95 Proceedings of the third ACM international
conference on Multimedia. ACM Digital Library, 1999, pp. 35–43.
[26] S. P. Rajendra and K. N, “A Survey of Automatic Video Summarization
Techniques,” International Journal of Electronics, Electrical and
Computational System (IJEECS), vol. 3, April 2014.
[27] N. Dimitrova, H.-J. Zhang, B.Shahraray, I. Sezan, T. Huang, and A.
Zakhor, “Applications of video-content analysis and retrieval,” in IEEE
Multimedia, IEEE, Ed., 2002.
[1] B. T. Truong and S. Venkatesh, “Video Abstraction: A Systematic
Review and Classification,” ACM Transactions on Multimedia
Computing, Communications, and Applications (TOMM), vol. 3, no. 3,
February 2007.
[2] E. Asadi and N. M. Charkari, “Video Summarization Using Fuzzy CMeans
Clustering,” in 20th Iranian Conference on Electrical
Engineering, (ICEE2012). IEEE, 15-17 May 2012, pp. 690 – 694.
[3] Z. Xiong, R. Radhakrishnan, A. Divakaran, Y. Rui, and T. S. Huang, A
Unified Framework for Video Summarization, Browsing Retrieval: with
Applications to Consumer and Surveillance Video. Academic
Press.2006.
[4] T. Mei, L.-X. Tang, J. Tang, and X.-S. Hua, “Near-Lossless Semantic
Video Summarization and Its Applications to Video Analysis,” ACM
Trans. Multimedia Computing Communications and Applications, June
2013.
[5] E. J. Y. C. Cahuina and G. C. Chavez, “A New Method for Static Video
Summarization Using Local Descriptors and Video Temporal
Segmentation,” in 26th Conference on Graphics, Patterns and Images
(SIBGRAPI). IEEE, 5-8 Aug 2013, pp. 226–233.
[6] E. Mendi, H. B. Clemente, and C. Bayrak, “Sports video summarization
based on motion analysis,” Computers and Electrical Engineering, vol.
39, pp. 790–796, April 2013.
[7] E. Mendi and C. Bayrak, “Shot Boundary Detection and Key Frame
Extraction using Salient Region Detection and Structural Similarity,” in
ACM SE ’10 Proceedings of the 48th Annual Southeast Regional
Conference, no. 66, 2010.
[8] E. J. Y. Cayllahua-Cahuina, G. Camara-Chavez, and D. Menotti, “A
static video summarization approach with automatic shot detection using
color histograms,” 2012.
[9] M. K.M., G. N.M., and I. M.A., “VGRAPH: An Effective Approach for
Generating Static Video Summaries,” in IEEE International Conference
on Computer Vision Workshops (ICCVW). IEEE, 2-8 Dec 2013, pp.
811 – 818.
[10] J. Li, “Video Shot Segmentation and Key Frame Extraction Based on
SIFT Feature,” in 2012 International Conference on Image Analysis and
Signal Processing (IASP). IEEE, 9-11 Nov 2012, pp. 1–8.
[11] L. D.G., “Object Recognition from Local Scale-Invariant Features,” in
The Proceedings of the Seventh IEEE International Conference on
Computer Vision, 1999, vol. 2. IEEE, 20-27 Sep 1999, pp. 1150–1157.
[12] Y. Tabii and R. O. H. Thami, “A new method for soccer video
summarization based on shot detection, classification and finite state
machine,” in SETIT 2009 5th International Conference: Sciences of
Electronic, Technologies of Information and Telecommunications, 22-26
March 2009.
[13] X. Sun and M. S. Kankanhalli, “Video Summarization Using RSequences,”
Real-Time Imaging, vol. 6, pp. 449–459, December 2000.
[14] J. Hou, J. Kang, and N. Qi, On Vocabulary Size in Bag-of-Visual-
Words Representation, ser. Lecture Notes in Computer Science, 21-24
September 2010, vol. 6297, pp. 414–424.
[15] Z. Yuan, T. Lu, D. Wu, and H. Y. Yu Huang, “Video Summarization
with Semantic Concept Preservation,” in MUM ’11 Proceedings of the
10th International Conference on Mobile and Ubiquitous Multimedia,
2011, pp. 109–112.
[16] V. N. and L. A., “Bayesian Modeling of Video Editing and Structure:
Semantic features for Video Summarization and Browsing,” in
Proceedings of 1998 International Conference on Image Processing.
ICIP 98, vol. 3. IEEE, 4-7 Oct 1998, pp. 153–157. [17] Cvetkovic, S. Jelenkovic, and S. V. M. Nikolic, “Video summarization
using color features and efficient adaptive threshold technique,”
Przeglad Elektrotechniczny, vol. R. 89, nr 2a, pp. 247 – 250, 2013.
[18] N. Ejaza, T. B. Tariqb, and S. W. Baika, “Adaptive key frame extraction
for video summarization using an aggregation mechanism,” Journal of
Visual Communication and Image Representation, vol. 23, no. 7,
pp.1031–1040, October 2012.
[19] M. Sophie, G. Mick¨ael, and P. Denis, “Résumé de vidéo à partir d’un
modèle d’attention visuelle,” in GRETSI - Actes de Colloque, G.
d’Etudes du Traitement du Signal et des Images, Ed., 2007.
[20] M. S. Lew, N. Sebe, C. Djeraba, and R. Jain, “Content-Based
Multimedia Information Retrieval: State of the Art and Challenges,”
ACM Transactions on Multimedia Computing, Communications, and
Applications (TOMM), vol. 2, pp. 1–9, February 2006.
[21] Y.-F. Ma and H.-J. Zhang, “A model of motion attention for video
skimming,” in Proceedings. International Conference on Image
Processing, vol. 1. IEEE, 2002, pp. 129–132.
[22] S. Zhu, Z. Liang, and Y. Liu, Automatic Video Abstraction via the
Progress of Story, ser. Lecture Notes in Computer Science. Springer
Berlin Heidelberg, 2010, vol. 6297, pp. 308–318.
[23] R. Laganière, R. Bacco, A. Hocevar, P. Lambert, G. Païs, and B. E.
Ionescu, “Video summarization from spatio-temporal features,” in
TVS’08 Proceedings of the 2nd ACM TRECVid Video Summarization
Workshop, 2008, pp. 144–148.
[24] Y. Gao, W.-B. Wang, J.-H. Yong and H.-J. Gu, “Dynamic video
summarization using two-level redundancy detection,” Multimedia
Tools and Applications, vol. 42, pp. 233–250, April 2009.
[25] M. G. Brown, J. T. Foote, G. J. F. Jones, K. S. Jones, and S. J. Young,
“Automatic content-based retrieval of broadcast news,” in
MULTIMEDIA ’95 Proceedings of the third ACM international
conference on Multimedia. ACM Digital Library, 1999, pp. 35–43.
[26] S. P. Rajendra and K. N, “A Survey of Automatic Video Summarization
Techniques,” International Journal of Electronics, Electrical and
Computational System (IJEECS), vol. 3, April 2014.
[27] N. Dimitrova, H.-J. Zhang, B.Shahraray, I. Sezan, T. Huang, and A.
Zakhor, “Applications of video-content analysis and retrieval,” in IEEE
Multimedia, IEEE, Ed., 2002.
@article{"International Journal of Information, Control and Computer Sciences:69495", author = "Zaynab Elkhattabi and Youness Tabii and Abdelhamid Benkaddour", title = "Video Summarization: Techniques and Applications", abstract = "Nowadays, huge amount of multimedia repositories
make the browsing, retrieval and delivery of video contents very slow
and even difficult tasks. Video summarization has been proposed to
improve faster browsing of large video collections and more efficient
content indexing and access. In this paper, we focus on approaches to
video summarization. The video summaries can be generated in many
different forms. However, two fundamentals ways to generate
summaries are static and dynamic. We present different techniques
for each mode in the literature and describe some features used for
generating video summaries. We conclude with perspective for
further research.
", keywords = "Semantic features, static summarization, video
skimming, Video summarization.", volume = "9", number = "4", pages = "928-6", }
