access icon free Ontology reasoning scheme for constructing meaningful sports video summarisation

As digital sports video becomes increasingly pervasive, semantic video summary becomes one of the important components for the next generation of multimedia applications. Ontology is a feasible way to mine the semantic information from the video stream. However, current ontology-based methods did not concentrate on the effectiveness and soundness of semantic reasoning. Here, the authors propose a content-directed ontology reasoning approach to produce meaningful sports video summarisation. The proposed ontology can facilitate the metadata acquisition of video and the improvement of query performance. It also provides a flexible way to query the sports video database, which cannot be achieved by simple keyword search. For annotating, describing and managing the sports video content, we propose a sports video descriptive language (SVDL) based on the proposed ontology. Moreover, the semantically meaningful sports video abstraction is produced by reasoning engine which is based on the extension of the Tableau algorithm. Meanwhile, the soundness and completeness of the reasoning algorithm can be solidly proved. Subjective assessment experimental results reveal the reliability and efficiency of the propose scheme.

Inspec keywords: data mining; video retrieval; video streaming; meta data; query languages; content management; inference mechanisms; ontologies (artificial intelligence); sport

Other keywords: metadata acquisition; sports video descriptive language; pervasive video summary; next generation multimedia applications; sports video database query; semantic video summary; sports video content management; semantic information mining; query performance improvement; content-directed ontology reasoning approach; reasoning engine; digital sports video; semantic reasoning; Tableau algorithm; meaningful sports video summarisation; video streaming; SVDL

Subjects: Optical, image and video signal processing; Information retrieval techniques; Information networks; Multimedia; Knowledge engineering techniques; Video signal processing; Humanities computing

References

    1. 1)
      • 24. Simou, N., Saathoff, C., Dasiopoulou, S., et al: ‘An ontology infrastructure for multimedia reasoning’. Proc. Int. Workshop on Very Low Bitrate Video Coding, 2005, pp. 5160.
    2. 2)
      • 14. Simou, N., Tzouvaras, V., Avrithis, Y., et al: ‘A visual descriptor ontology for multimedia reasoning’. Proc. Workshop on Image Analysis for Multimedia Interactive Services.
    3. 3)
      • 11. Carbonaro, A.: ‘Ontology-based Video Retrieval in a Semantic-based Learning Environment’, J. e-Learn. Knowl. Soc., 2008, 4, (3), pp. 203212.
    4. 4)
      • 4. Oskouie, P., Alipour, S., Eftekhari-Moghadam, A.-M.: ‘Multimodal feature extraction and fusion for semantic mining of soccer video: a survey’, Artif. Intell. Rev., 2012, 16, (6), pp. 345379.
    5. 5)
      • 12. Mezaris, V., Kompatsiaris, I., Boulgouris, N.V., et al: ‘Real-time compressed domain spatiotemporal segmentation and ontologies for video indexing and retrieval’, IEEE Trans. Circuits Syst. Video Technol., 2004, 14, (5), pp. 606621 (doi: 10.1109/TCSVT.2004.826768).
    6. 6)
      • 29. Xu, C., Wang, J., Lu, H., et al: ‘A novel framework for semantic annotation and personalized retrieval of sports video’, IEEE Trans. Multimedia, 2008, 10, (3), pp. 421436 (doi: 10.1109/TMM.2008.917346).
    7. 7)
      • 19. Simoff, J.S.M.L.: ‘Maher, Ontology-based multimedia data mining for design information retrieval’. Proc. Int. Computing Congress, 1998, pp. 212223.
    8. 8)
      • 5. D'Orazio, T., Leo, M., Spagnolo, P., Nitti, M., Mosca, N.: ‘A visual system for real time detection of goal events during soccer matches’, Comput. Vis. Image Underst., 2009, 113, pp. 622632 (doi: 10.1016/j.cviu.2008.01.010).
    9. 9)
      • 23. Francois, A.R., Nevatia, R., Hobbs, J., et al: ‘VERL: an ontology framework for representing and annotating video events’, IEEE Multimedia Mag., 2005, 12, (4), pp. 7686 (doi: 10.1109/MMUL.2005.87).
    10. 10)
      • 13. James, N., Todorov, K., Hudelot, C.: ‘Ontology matching for the semantic annotation of images’. IEEE Inter. Conf. on Fuzzy Systems, 2010, pp. 24992506.
    11. 11)
      • 16. Scherp, A., Franz, T., Saathoff, C., et al: ‘A model of events based on a foundational ontology’. University of Koblenz-Landau, Technical report 02/2009, 2009.
    12. 12)
      • 9. Bao, J., Cao, Y., Tavanapong, W.: ‘Integration of domain-specific and domain-independent ontologies for colonoscopy video database annotation’. Proc. Int. Conf. on Information and Knowledge Engineing, 2004, pp. 8288.
    13. 13)
      • 26. Harit, G., Chaudhury, S., Ghosh, H.: ‘Using Multimedia Ontology for generating conceptual annotations and hyperlinks in video collections’. Int. Conf. Web Intelligence, 2006.
    14. 14)
      • 18. Perperis, T., Giannakopoulos, T., Makris, A.: ‘Multimodal and ontology-based fusion approaches of audio and visual processing for violence detection in movies’, Expert Syst. Appl., 2011, 38, (11), pp. 1410214116.
    15. 15)
      • 7. Ballan, L., Bertini, M., Del Bimbo, A., et al: ‘Video annotation and retrieval using ontologies and rule learning’, IEEE Multimedia, 2010, 46, (2–3), pp. 331370.
    16. 16)
      • 1. Schmidt-Schauß, M., Smolka, G.: ‘Attributive concept descriptions with complements’, Artif. Intell., 1991, 48, (1), pp. 126 (doi: 10.1016/0004-3702(91)90078-X).
    17. 17)
      • 20. Petrushin, V.A., Khan, L.: ‘Multimedia data mining and knowledge discovery’ (Springer-Verlag, 2007).
    18. 18)
      • 15. Liang, B., Songyang, L., Jones, G.J.F., et al: ‘Video semantic content analysis based on ontology’. 11th Int. Machine Vision and Image Processing Conf., 2007, pp. 57.
    19. 19)
      • 6. Zhu, G., Xu, C., Huang, Q., et al: ‘Event tactic analysis based on broadcast sports video’, IEEE Trans. Multimedia, 2009, 11, (1), pp. 4967 (doi: 10.1109/TMM.2008.2008918).
    20. 20)
      • 10. Zhu, X.Q., Fan, J., Elmagarmid, A.: ‘Hierarchical video content description and summarization using unified semantic and visual similarity’, Multimedia Syst., 2003, 9, (1), pp. 3153 (doi: 10.1007/s00530-003-0076-5).
    21. 21)
      • 32. http://protege.stanford.edu/.
    22. 22)
      • 27. Castano, S., Espinosa, S., Ferrara, A., et al: ‘Ontology dynamics with multimedia information: the BOEMIE evolution methodology’. Int. Workshop on Ontology Dynamics, 2007.
    23. 23)
      • 22. Dasiopoulou, S., Tzouvaras, V., Kompatsiaris, I., et al: ‘Enquiring MPEG-7 based multimedia ontologies’, Multimedia Tools Appl., 2010, 46, (2), pp. 331370 (doi: 10.1007/s11042-009-0387-4).
    24. 24)
      • 31. Dijkstra, E.W.: ‘On the role of scientific thought’, in Gries, D. (Ed.): ‘Selected writings on computing: a personal perspective’ (Springer-Verlag, 1982), pp. 6066.
    25. 25)
      • 21. Tsinaraki, C., Polydoros, P., Kazasis, F., et al: ‘Ontology-based semantic indexing for MPEG-7 and TV-anytime audiovisual content’, Multimedia Tools Appl., 2005, 26, (3), pp. 299325 (doi: 10.1007/s11042-005-0894-x).
    26. 26)
      • 35. Lutz, C., Milicic, M.: ‘Description logics with concrete domains and functional dependencies’. LTCS-Report 04-06, 2004.
    27. 27)
      • 33. Baader, F., Nutt, W.: ‘Basic description logic’, in Baader, F., et al., (Ed.): ‘The description logic handbook: theory, implementation and applications’ (Cambridge University Press, 2002).
    28. 28)
      • 8. Qian, X., Wang, H., Liu, G., Hou, X.: ‘A novel approach for soccer video summarization’. Second Int. Conf. Multimedia and Information Technology, 2010, pp. 138141.
    29. 29)
      • 28. Zhai, G., Fox, G.C., Pierce, M., et al: ‘eSports: collaborative and synchronous video annotation system in grid computing environment’. Seventh IEEE Int. Symp. Multimedia, 2005, pp. 95103.
    30. 30)
      • 34. Achille, V.C.: ‘Spatial reasoning and ontology: parts, wholes, and locations’, Aiello, M., et al, (Ed.): ‘Handbook of spatial logics’ (Springer-Verlag, 2007), pp. 9451038.
    31. 31)
      • 36. Ouyang, J.-Q., Li, J.-T., Tang, H.-R.: ‘Interactive key frame selection model’, J. Vis. Commun. Image Represent., 2006, 17, (6), pp. 11451163 (doi: 10.1016/j.jvcir.2006.03.003).
    32. 32)
      • 25. Saathoff, C., Scherp, A.: ‘Unlocking the semantics of multimedia presentations in the web with the multimedia metadata ontology’. 19th WWW, 2010, pp. 831840.
    33. 33)
      • 3. Money, A.G., Agius, H.: ‘Video summarization: a conceptual framework and survey of the state of the art’, J. Vis. Commun. Image Represent., 2008, 19, (2), pp. 121143 (doi: 10.1016/j.jvcir.2007.04.002).
    34. 34)
      • 30. Arndt, R., Troncy, R., Staab, S., et al: ‘COMM: designing a well-founded multimedia ontology for the web’. Sixth Inter. Semantic Web Conf., 2007, pp. 3042.
    35. 35)
      • 17. Xu, C., Cheng, J., Zhang, Y., et al: ‘Sports video analysis: semantics extraction, editorial content creation and adaptation’, J. Multimedia, 2009, 4, (2), pp. 6979.
    36. 36)
      • 2. Truong, B.T., Venkatesh, S.: ‘Video abstraction: a systematic review and classification’, ACM Trans. Multimedia Comput. Commun. Appl., 2007, 3, (1), pp. 137 (doi: 10.1145/1198302.1198305).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-ipr.2012.0495
Loading

Related content

content/journals/10.1049/iet-ipr.2012.0495
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading