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International Journal on Digital Libraries

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23.01.2020

Content selection criteria for news multi-video summarization based on human strategies

verfasst von: Tamires Tessarolli de Souza Barbieri, Rudinei Goularte

Erschienen in: International Journal on Digital Libraries | Ausgabe 1/2021

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Abstract

In the recent years, the multimedia data volume produced and available for access has increased continuously and quickly, notably video content. This context has also increased the overload information problem: finding content of interest in the huge amount of available options. So, efficient schemes for content access are needed. Automatic video summarization is a research field that deals with this problem. Furthermore, the current multimedia systems make available several videos related to the same topic but having, each one, a piece of unique complementary information. This fact highlights the need for multi-video summarization to deal with users’ interest in being informed about a subject from a set of videos without being obligated to watch the whole set. However, the literature analysis shows that human strategies are not considered to define criteria used to automatically select video segments that will compose a summary and the focus of techniques has been the identification of common information in different videos. In this work, we investigate human strategies for news multi-video summarization. The results of the study with real users uncover relevant criteria to develop summaries, with potential to increase their semantics and bring them closer to users’ perception.

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Almeida, J., Leite, N.J., da Silva Torres, R.: Online video summarization on compressed domain. J. Vis. Commun. Image Represent. 24(6), 729–738 (2013). https://doi.org/10.1016/j.jvcir.2012.01.009CrossRef

Camargo, R.T., Di-Felippo, A., Pardo, T.A.S.: On strategies of human multi-document summarization. In: Proceedings of Symposium in Information and Human Language Technology, pp. 141–150. Sociedade Brasileira de Computação, Natal (2015)

Chen, F., De Vleeschouwer, C., Cavallaro, A.: Resource allocation for personalized video summarization. IEEE Trans. Multimed. 16(2), 455–469 (2014). https://doi.org/10.1109/TMM.2013.2291967CrossRef

Cisco: white paper: Cisco VNI forecast and methodology, 2015–2020 (2016). http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/complete-white-paper-c11-481360.html. Accessed 01 June 2017

Dale, K., Shechtman, E., Avidan, S., Pfister, H.: Multi-video browsing and summarization. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 1–8 (2012). https://doi.org/10.1109/CVPRW.2012.6239253

Groupon: why video should be a part of your 2015 marketing strategy (2014). https://www.groupon.co.uk/merchant/blog/why-video-should-be-a-part-of-your-2014-marketing-strategy. Accessed 01 June 2017

Gygli, M., Grabner, H., Riemenschneider, H., Van Gool, L.: Creating summaries from user videos. In: Computer Vision—ECCV 2014, Lecture Notes in Computer Science, vol. 8695, pp. 505–520. Springer International Publishing (2014). https://doi.org/10.1007/978-3-319-10584-0_33

Hong, R., Tang, J., Tan, H.K., Yan, S., Ngo, C., Chua, T.S.: Event driven summarization for web videos. In: Proceedings of the first SIGMM workshop on social media, WSM ’09, pp. 43–48. ACM, New York (2009). https://doi.org/10.1145/1631144.1631154

Ide, I., Zhang, Y., Tanishige, R., Doman, K., Kawanishi, Y., Deguchi, D., Murase, H.: Summarization of news videos considering the consistency of auditory and visual contents. In: 2017 IEEE International Symposium on Multimedia (ISM), pp. 193–199 (2017). https://doi.org/10.1109/ISM.2017.33

10.

Ji, Z., Zhang, Y., Pang, Y., Li, X.: Hypergraph dominant set based multi-video summarization. Signal Process. 148(C), 114–123 (2018). https://doi.org/10.1016/j.sigpro.2018.01.028CrossRef

11.

Kanehira, A., Van Gool, L., Ushiku, Y., Harada, T.: Viewpoint-aware video summarization. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7435–7444 (2018). https://doi.org/10.1109/CVPR.2018.00776

12.

Kannan, R., Ghinea, G., Swaminathan, S., Kannaiyan, S.: Improving video summarization based on user preferences. In: Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), pp. 1–4 (2013). https://doi.org/10.1109/NCVPRIPG.2013.6776187

13.

Li, Y., Merialdo, B.: Multi-video summarization based on AV-MMR. In: International Workshop on Content-Based Multimedia Indexing (CBMI), pp. 1–6 (2010). https://doi.org/10.1109/CBMI.2010.5529899

14.

Li, Y., Merialdo, B.: Multi-video summarization based on video-MMR. In: 11th International Workshop on Image Analysis for Multimedia Interactive Services WIAMIS 10, pp. 1–4 (2010)

15.

Li, Y., Merialdo, B.: Multi-video summarization based on OB-MMR. In: 9th International Workshop on Content-Based Multimedia Indexing (CBMI), pp. 163–168 (2011). https://doi.org/10.1109/CBMI.2011.5972539

16.

Li, Y., Merialdo, B.: Video Summarization Based on Balanced AV-MMR, pp. 370–382. Springer, Berlin (2012). https://doi.org/10.1007/978-3-642-27355-1_35

17.

Li, Y., Merialdo, B.: Multimedia maximal marginal relevance for multi-video summarization. Multimed Tools Appl. 75(1), 199–220 (2016). https://doi.org/10.1007/s11042-014-2287-5CrossRef

18.

Li, Y., Merialdo, B., Rouvier, M., Linares, G.: Static and dynamic video summaries. In: Proceedings of the 19th ACM International Conference on Multimedia, MM ’11, pp. 1573–1576. ACM, New York (2011). https://doi.org/10.1145/2072298.2072068

19.

Netflix: About Netflix - Netflix has been leading the way for digital content since 1997 (2019). https://media.netflix.com/en/about-netflix. Accessed 30 Apr 2019

20.

Nie, L., Hong, R., Zhang, L., Xia, Y., Tao, D., Sebe, N.: Perceptual attributes optimization for multivideo summarization. IEEE Trans. Cybern. 46(12), 2991–3003 (2016). https://doi.org/10.1109/TCYB.2015.2493558CrossRef

21.

Nielsen, J.: how many test users in a usability study? (2012). https://www.nngroup.com/articles/how-many-test-users/. Accessed 12 Sep 2019

22.

Ou, S.H., Lee, C.H., Somayazulu, V.S., Chen, Y.K., Chien, S.Y.: On-line multi-view video summarization for wireless video sensor network. IEEE J. Sel. Top. Signal Process. 9(1), 165–179 (2015). https://doi.org/10.1109/JSTSP.2014.2331916CrossRef

23.

Ou, S.H., Lu, Y.C., Wang, J.P., Chien, S.Y., Lin, S.D., Yeti, M.Y., Lee, C.H., Gibbons, P.B., Somayazulu, V.S., Chen, Y.K.: Communication-efficient multi-view keyframe extraction in distributed video sensors. In: IEEE Visual Communications and Image Processing Conference, pp. 13–16 (2014). https://doi.org/10.1109/VCIP.2014.7051492

24.

Panda, R., Mithun, N.C., Roy-Chowdhury, A.K.: Diversity-aware multi-video summarization. IEEE Trans. Image Process. 26(10), 4712–4724 (2017). https://doi.org/10.1109/TIP.2017.2708902MathSciNetCrossRef

25.

Panda, R., Roy-Chowdhury, A.K.: Collaborative summarization of topic-related videos. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4274–4283 (2017). https://doi.org/10.1109/CVPR.2017.455

26.

Petrie, H., Bevan, N.: The Evaluation of Accessibility, Usability, and User Experience, pp. 1–30. CRC Press, Boca Raton (2009)

27.

Potapov, D., Douze, M., Harchaoui, Z., Schmid, C.: Category-Specific Video Summarization. In: Computer Vision – ECCV 2014, Lecture Notes in Computer Science, vol. 8694, pp. 540–555. Springer International Publishing (2014). https://doi.org/10.1007/978-3-319-10599-4_35

28.

Preece, J., Rogers, Y., Sharp, H.: Interaction Design: Beyond Human-Computer Interaction, 1st edn. John Wiley & Sons, New York (2002)

29.

Rajendra, S.P., Keshaveni, N.: A survey of automatic video summarization techniques. Int. J. Electron. Electr. Comput. Syst. 3(1), 1–6 (2014)CrossRef

30.

Sears, A., Hanson, V.L.: Representing users in accessibility research. ACM Trans. Access. Comput. 4(2), 7:1–7:6 (2012). https://doi.org/10.1145/2141943.2141945CrossRef

31.

Shao, J., Jiang, D., Wang, M., Chen, H., Yao, L.: Multi-video summarization using complex graph clustering and mining. Comput. Sci. Inf. Syst. 7(1), 85–98 (2010)CrossRef

32.

Toffler, A.: Future Shock, 1st edn. Bantam, New York (1984)

33.

Truong, B.T., Venkatesh, S.: Video abstraction: a systematic review and classification. ACM Trans. Multimed. Comput. Commun. Appl. 3(1), 3 (2007). https://doi.org/10.1145/1198302.1198305CrossRef

34.

Wang, F., Merialdo, B.: Multi-document video summarization. In: IEEE International Conference on Multimedia and Expo, pp. 1326–1329 (2009). https://doi.org/10.1109/ICME.2009.5202747

35.

Wang, M., Hong, R., Li, G., Zha, Z.J., Yan, S., Chua, T.S.: Event driven web video summarization by tag localization and key-shot identification. IEEE Trans. Multimed. 14(4), 975–985 (2012). https://doi.org/10.1109/TMM.2012.2185041CrossRef

36.

Yoshitaka, A., Sawada, K.: Personalized video summarization based on behavior of viewer. In: Eighth International Conference on Signal Image Technology and Internet Based Systems (SITIS), pp. 661–667 (2012). https://doi.org/10.1109/SITIS.2012.100

37.

YouTube: statistics-global reach (2019). https://www.youtube.com/yt/press/statistics.html. Accessed 30 Apr 2019

38.

Zhang, L., Gao, Y., Hong, R., Hu, Y., Ji, R., Dai, Q.: Probabilistic skimlets fusion for summarizing multiple consumer landmark videos. IEEE Trans. Multimed. 17(1), 40–49 (2015). https://doi.org/10.1109/TMM.2014.2370257CrossRef

39.

Zhang, L., Xia, Y., Mao, K., Ma, H., Shan, Z.: An effective video summarization framework toward handheld devices. IEEE Trans. Ind. Electron. 62(2), 1309–1316 (2015). https://doi.org/10.1109/TIE.2014.2336639CrossRef

40.

Zhang, Y., Ma, C., Zhang, J., Zhang, D., Liu, Y.: An interactive personalized video summarization based on sketches. In: Proceedings of the 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry, VRCAI ’13, pp. 249–258. ACM, New York (2013). https://doi.org/10.1145/2534329.2534343

41.

Zhang, Y., Ma, H., Zimmermann, R.: Dynamic multi-video summarization of sensor-rich videos in geo-space, pp. 380–390. Springer, Berlin (2013). https://doi.org/10.1007/978-3-642-35725-1_35

42.

Zhang, Y., Wang, G., Seo, B., Zimmermann, R.: Multi-video summary and skim generation of sensor-rich videos in geo-space. In: Proceedings of the 3rd Multimedia Systems Conference, MMSys ’12, pp. 53–64. ACM, New York (2012). https://doi.org/10.1145/2155555.2155565

43.

Zhang, Y., Zhang, L., Zimmermann, R.: Aesthetics-guided summarization from multiple user generated videos. ACM Trans. Multimed. Comput. Commun. Appl. 11(2), 24:1–24:23 (2015). https://doi.org/10.1145/2659520CrossRef

44.

Zhang, Y., Zimmermann, R.: Efficient summarization from multiple georeferenced user-generated videos. IEEE Trans. Multimed. 18(3), 418–431 (2016). https://doi.org/10.1109/TMM.2016.2520827CrossRef

45.

Zhu, J., Liao, S., Li, S.Z.: Multicamera joint video synopsis. IEEE Trans. Circuits Syst. Video Technol. 26(6), 1058–1069 (2016). https://doi.org/10.1109/TCSVT.2015.2430692CrossRef

Titel: Content selection criteria for news multi-video summarization based on human strategies
verfasst von: Tamires Tessarolli de Souza Barbieri
Rudinei Goularte
Publikationsdatum: 23.01.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal on Digital Libraries / Ausgabe 1/2021
Print ISSN: 1432-5012
Elektronische ISSN: 1432-1300
DOI: https://doi.org/10.1007/s00799-020-00281-9

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