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CONTENTUS—technologies for next generation multimedia libraries

Automatic multimedia processing for semantic search

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Abstract

An ever-growing amount of digitized content urges libraries and archives to integrate new media types from a large number of origins such as publishers, record labels and film archives, into their existing collections. This is a challenging task, since the multimedia content itself as well as the associated metadata is inherently heterogeneous—the different sources lead to different data structures, data quality and trustworthiness. This paper presents the contentus approach towards an automated media processing chain for cultural heritage organizations and content holders. Our workflow allows for unattended processing from media ingest to availability thorough our search and retrieval interface. We aim to provide a set of tools for the processing of digitized print media, audio/visual, speech and musical recordings. Media specific functionalities include quality control for digitization of still image and audio/visual media and restoration of the most common quality issues encountered with these media. Furthermore, the contentus tools include modules for content analysis like segmentation of printed, audio and audio/visual media, optical character recognition (OCR), speech-to-text transcription, speaker recognition and the extraction of musical features from audio recordings, all aimed at a textual representation of information inherent within the media assets. Once the information is extracted and transcribed in textual form, media independent processing modules offer extraction and disambiguation of named entities and text classification. All contentus modules are designed to be flexibly recombined within a scalable workflow environment using cloud computing techniques. In the next step analyzed media assets can be retrieved and consumed through a search interface using all available metadata. The search engine combines Semantic Web technologies for representing relations between the media and entities such as persons, locations and organizations with a full-text approach for searching within transcribed information gathered through the preceding processing steps. The contentus unified search interface integrates text, images, audio and audio/visual content. Queries can be narrowed and expanded in an exploratory manner, search results can be refined by disambiguating entities and topics. Further, semantic relationships become not only apparent, but can also be navigated.

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References

  1. Agius HW, Angelides MC (2009) From mpeg-7 user interaction tools to hanging basket models: bridging the gap. Multimedia Tools Appl 41(3):375–406

    Article  Google Scholar 

  2. ALEXANDRIA—a collaborative knowledge engine, a use case of the Theseus research program. http://alexandria.wefind.de. Accessed 1 Dec 2011

  3. Altenhöner R, Hannemann J, Kett J (2010) Linked data aus und für bibliotheken: rückgratstärkung im Semantic Web. In: Proc of 1. DGI-Konferenz Semantic Web und linked data—elemente zukünftiger informationsstrukturen, pp 67–75

  4. Amato G, Debole F, Peters CPS (2008) The multimatch prototype: multilingual/multimedia search for cultural heritage objects. In: Proc of the 12th European conf on digital libraries. Aarhus, Denmark

    Google Scholar 

  5. Antonacopoulos A, Pletschacher S, Bridson D, Papadopoulos C (2009) Page segmentation competition. In: Proc of 10th int conf on document analysis and recognition (ICDAR), pp 1370–1374

  6. Avrithis Y, Kompatsiaris Y, Staab S, O’Connor N (eds) (2006) Semantic multimedia: first international conference on semantic and digital media technologies. In: SAMT 2006, Athens, Greece, 6–8 December 2006, Proceedings, lecture notes in computer science, vol 4306. Springer, Berlin. doi:10.1007/11930334

  7. Bartolini I, Patella M, Romani C (2010) Shiatsu: semantic-based hierarchical automatic tagging of videos by segmentation using cuts. In: Proc of the 3rd int’l workshop on automated information extraction in media production, AIEMPro ’10. ACM, New York, pp 57–62

    Chapter  Google Scholar 

  8. Baum D (2009) Topic-based speaker recognition for German parliamentary speeches. In: Proc of IEEE automatic speech recognition and understanding workshop (ASRU ’09). Merano, Italy

    Google Scholar 

  9. Baum D, Schneider D, Bardeli R, Schwenninger J, Samlowski B, Winkler T, Köhler J (2010) DiSCo—a German evaluation corpus for challenging problems in the broadcast domain. In: Proc of the 7th int’l conf on language resources and evaluation (LREC’10)

  10. Baum D, Schneider D, Mertens T, Köhler J (2010) Constrained subword units for speaker recognition. In: Proc of the speaker and language recognition workshop odyssey

  11. Behrens-Neumann R, Pfeifer B (2011) Die Gemeinsame Normdatei—ein Kooperationsprojekt. Dialog mit Bibliotheken

  12. Benitez AB, Zhong D, Chang SF (2007) Enabling MPEG-7 structural and semantic descriptions in retrieval applications. J Am Soc Inf Sci Technol 58:1377–1380

    Article  Google Scholar 

  13. Berners-Lee T, Hendler J, Lassila O (2001) The semantic Web. Sci Am 284(5):34–43

    Article  Google Scholar 

  14. Blinkx: a video search engine. http://www.blinkx.com. Accessed 1 Dec 2011

  15. Breuel T (2002) Two algorithms for geometric layout analysis. In: Proc of workshop on document analysis systems, vol 3697, pp 188–199

  16. Breuel TM (2003) High performance document layout analysis

  17. Broadcast metadata exchange format—specification. http://www.irt.de/en/activities/production/bmf.html. Accessed 1 Dec 2011

  18. Celma O, Dasiopoulou S, Hausenblas M, Little S, Tsinaraki C, Troncy R (2007) MPEG-7 and the semantic Web. W3C Incubator Group Editors

  19. Cheng S, Wang H, Fu H (2010) BIC-based speaker segmentation using divide-and-conquer strategies with application to speaker diarization. IEEE Trans Audio Speech Lang Process 18(1):141–157

    Article  Google Scholar 

  20. Contentus: a use case of the Theseus research program. http://www.contentus-projekt.de. Accessed 1 Dec 2011

  21. Corda U (2008) Multimedia semantics—from MPEG-7 metadata to semantic Web ontologies

  22. Dasiopoulou S, Tzouvaras V, Kompatsiaris I, Strintzis MG (2009) Capturing MPEG-7 semantics. In: Sicilia MA, Lytras MD (eds) Metadata and semantics. Springer, New York, pp 113–122

    Chapter  Google Scholar 

  23. Dasiopoulou S, Giannakidou E, Litos G, Malasioti P, Kompatsiaris Y (2011) Knowledge-driven multimedia information extraction and ontology evolution. Chap A survey of semantic image and video annotation tools. Springer, Berlin, pp 196–239

    Book  Google Scholar 

  24. DC (Dublin Core): metadata element set, version 1.1. http://purl.org/dc/elements/1.1/. Accessed 1 Dec 2011

  25. DDB: the German Digital Library project, a portal for culture and science. http://www.deutsche-digitale-bibliothek.de. Accessed 1 Dec 2011

  26. Debald S, Nejdl W, Nucci FS, Paiu R, Plu M (2006) Pharos—platform for search of audiovisual resources across online spaces. In: Proc of the 1st int’l conf on semantic and digital media technologies (SAMT2006). Athens, Greece

  27. Defining N-ary relations on the semantic Web, W3C working group note 12 April 2006. http://www.w3.org/TR/swbp-n-aryRelations/. Accessed 1 Dec 2011

  28. Ding H, Sølvberg IT (2005) Semantic data integration framework in peer-to-peer based digital libraries. JDIM 3(2):71–75

    Google Scholar 

  29. dpa (deutsche presse-agentur gmbh). http://www.dpa.de. Accessed 1 Dec 2011

  30. FAO (Food and Agriculture Organization of the United Nations): geopolitical ontology. http://aims.fao.org/aos/geopolitical.owl. Accessed 1 Dec 2011

  31. Ferzli R, Karam LJ (2009) A no-reference objective image sharpness metric based on the notion of just noticeable blur (jnb). IEEE Trans Image Process 18(4):717–728

    Article  MathSciNet  Google Scholar 

  32. FOAF (Friend Of A Friend): vocabulary specification. http://xmlns.com/foaf/spec/. Accessed 1 Dec 2011

  33. Gatos B, Danatsas D, Pratikakis I, Perantonis SJ (2005) Automatic table detection in document images. In: Proc of 3rd int conf on advances in pattern recognition (ICAPR), LNCS 3686, pp 609–618

  34. Goldberg D, Nichols D, Oki BM, Terry D (1992) Using collaborative filtering to weave an information tapestry. Commun ACM 35:61–70

    Article  Google Scholar 

  35. Guha R, McCool R, Miller E (2003) Using the semantic Web: semantic search. In: WWW ’05 proceedings of the 14th international conference on world wide Web, pp 700–709. doi:10.1145/775152.775250

  36. Hannemann J, Kett J (2010) Linked data for libraries. In: Proc of the world library and information congress of the Int’l Federation of Library Associations and Institutions (IFLA)

  37. Hinze A, Buchanan G, Bainbridge D, Witten IH (2009) Semantics in Greenstone. In: Kruk SR, McDaniel B (eds) Semantic digital libraries. Springer, New York, pp 163–176. doi:10.1007/978-3-540-85434-0_12

    Chapter  Google Scholar 

  38. Hobson P, Kompatsiaris Y (2006) Advances in semantic multimedia analysis for personalised content access. In: ISCAS. IEEE, Piscataway

    Google Scholar 

  39. Huiskes MJ, Lew MS (2008) The Mir Flickr retrieval evaluation. In: Proceeding of the 1st ACM int’l conf on multimedia information retrieval, MIR ’08. ACM, New York, pp 39–43

    Chapter  Google Scholar 

  40. IASA (International Association of Sound and Audiovisual Archives) TC 04: guidelines on the production and preservation of digital audio objects. http://www.iasa-web.org/audio-preservation-tc04. Accessed 1 Dec 2011

  41. Information technology—multimedia content description interface—part 1: systems. http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=34228. Accessed 1 Dec 2011

  42. Informedia-i: integrated speech, image and language understanding for creation and exploration of digital video libraries. http://www.informedia.cs.cmu.edu/dli1/index.html. Accessed 1 Dec 2011

  43. Informedia-ii digital video library: auto summarization and visualization across multiple video documents and libraries. http://www.informedia.cs.cmu.edu/dli2/index.html. Accessed 1 Dec 2011

  44. Jain A, Yu B (1998) Document representation and its application to page decomposition. IEEE Trans Pattern Anal Mach Intell 20(3):294–308

    Article  Google Scholar 

  45. Kaprykowsky H, Ndjiki-Nya P (2009) Restoration of digitized videos: efficient drop-out detection and removal. In: Proc of IEEE int’l conf on image processing (ICIP ’09)

  46. Kim Hg, Moreau N, Sikora T (2005) MPEG-7 audio and retrieval. Communication

  47. Koeppel M, Doshkov D, Ndjiki-Nya P (2009) Fully automatic inpainting method for complex image content. In: Proc of int’l workshop on image analysis for multimedia interactive services (WIAMS’09)

  48. Kompatsiaris Y, Hobson P (2008) Semantic multimedia and ontologies: theory and applications, 1st edn.

  49. Konya I, Seibert C, Eickeler S, Glahn S (2009) Constant-time locally optimal adaptive binarization. In: Proc of 10th int’l conf document analysis and recognition. IEEE, Piscataway, pp 738–742

    Google Scholar 

  50. Lafferty J, McCallum A, Pereira F (2001) Conditional random fields: probabilistic models for segmenting and labeling sequence data. Williamstown, MA, USA, pp 282–289

  51. Lindbloom B (1994) Delta E (CIE 1994). In: Delta E (CIE 1994)

  52. Linked data service of the German National Library. http://www.d-nb.de/eng/hilfe/service/linked_data_service.htm. Accessed 1 Dec 2011

  53. Liu M, Konya I, Nandzik J, Flores-Herr N, Eickeler S, Ndjiki-Nya P (2011) A new quality assessment and improvement system for print media. EURASIP (Special issue on image and video quality improvement techniques for emerging applications), submitted

  54. Manjunath BS (2002) Introduction to MPEG-7, multimedia content description interface. Wiley, New York

    Google Scholar 

  55. MEDIAGLOBE—the digital archive, a SME project of the Theseus research program. http://www.projekt-mediaglobe.de/. Accessed 1 Dec 2011

  56. Mediamill—semantic video search engine. http://www.science.uva.nl/research/mediamill/index.php. Accessed 1 Dec 2011

  57. Mesh—multimedia semantic syndication for enhanced news services. http://www.mesh-ip.eu. Accessed 1 Dec 2011

  58. Messina A, Sutter RD, Bailer W, Sano M, Evain JP, Ndjiki-Nya P, Schroeter B (2010) MPEG-7 audiovisual description profile (avdp). Report MPEG2010/M17744, MPEG (ISO/IEC JTC1/SC29/WG11)

  59. METS—metadata encoding and transmission standard specification. http://www.loc.gov/standards/mets. Accessed 1 Dec 2011

  60. MODS—metadata object description schema specification. http://www.loc.gov/standards/mods. Accessed 1 Dec 2011

  61. Mufin player: a recommendation based music player. http://player.mufin.com/en. Accessed 1 Dec 2011

  62. Müller S, Bühler J, Weitbruch S, Thebault C, Doser I, Neisse O (2009) Scratch detection supported by coherency analysis of motion vector fields. In: ICIP’09, pp 89–92

  63. Nandzik J, Heß A, Hannemann J, Flores-Herr N, Bossert K (2010) Contentus—towards semantic multi-media libraries. In: Proc of 76th IFLA general conf and assembly (2010)

  64. NISO metadata for images in XML (NISO MIX) schema. http://www.loc.gov/standards/mix. Accessed 1 Dec 2011

  65. Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9(1):62–66

    Article  MathSciNet  Google Scholar 

  66. Petasis G, Karkaletsis V, Krithara A, Paliouras G, Spyropoulos C (2009) Semi-automated ontoloy learning: the Boemie approach. In: Proceedings of the 1st ESWC workshop on inductive reasoning and machine learning. Heraklion, Greece

    Google Scholar 

  67. Petersohn C (2004) Fraunhofer HHI at TRECVID 2004: shot boundary detection system. In: Proc TREC video retrieval evaluation workshop

  68. Petersohn C (2009) Temporal video structuring for preservation and annotation of video content. In: Proc of IEEE int’l conf on image processing (ICIP ’09)

  69. PND, name authority file of the German National Library. http://www.d-nb.de/eng/standardisierung/normdateien/pnd.htm. Accessed 1 Dec 2011

  70. Ratinov L, Roth D (2009) Design challenges and misconceptions in named entity recognition. Boulder, CO, USA, pp 147–155

  71. Reynolds DA, Quatieri TF, Dunn RB (2000) Speaker verification using adapted Gaussian mixture models. Digit Signal Process 10(1–3):19–41

    Article  Google Scholar 

  72. RDA (Resource Description and Access): vocabularies. http://metadataregistry.org/rdabrowse.htm. Accessed 1 Dec 2011

  73. RELATIONSHIP: a vocabulary for describing relationships between people. http://vocab.org/relationship/.html. Accessed 1 Dec 2011

  74. Rushes—European research project on multimedia search and retrieval of rushes data. http://www.rushes-project.eu. Accessed 1 Dec 2011

  75. Schneider D, Schon J, Eickeler S (2008) Towards large scale vocabulary independent spoken term detection: advances in the Fraunhofer IAIS audiomining system. In: Köhler J, Larson M, Jong de F, Kraaij W, Ordelman R (eds) Proc of the ACM SIGIR workshop “searching spontaneous conversational speech”. Singapore

  76. Skos (simple knowledge organization system): reference. http://www.w3.org/2004/02/skos/. Accessed 1 Dec 2011

  77. Smeaton AF, Over P, Kraaij W (2006) Evaluation campaigns and trecvid. In: Proc of the 8th ACM int’l workshop on multimedia information retrieval, MIR ’06. ACM, New York, pp 321–330

    Chapter  Google Scholar 

  78. Smith K (2006) Capturing analog sound for digital preservation: report of a roundtable discussion of best practices for transferring analog discs and tapes

  79. Snoek CGM, Worring M (2009) Concept-based video retrieval. Found Trends Inf Retr 4(2):215–322

    Google Scholar 

  80. Snoek CGM, Smeulders AWM (2010) Visual-concept search solved? IEEE Computer 43(6):76–78

    Article  Google Scholar 

  81. Su X, Khoshgoftaar TM (2009) A survey of collaborative filtering techniques. Adv Artif Intell 2009:1–19

    Article  MATH  Google Scholar 

  82. Theseus: a research program. http://www.theseus-programm.de. Accessed 1 Dec 2011

  83. Tritschler A, Gopinath RA (1999) Improved speaker segmentation and segments clustering using the Bayesian information criterion. In: Proc of 6th European conf on speech communication and technology (EUROSPEECH’99). Budapest, Hungary, pp 679–682

  84. Tsinaraki C, Christodoulakis S (2007) An MPEG-7 query language and a user preference model that allow semantic retrieval and filtering of multimedia content. Multimedia Syst 13(2):131–153

    Article  Google Scholar 

  85. Ulges A, Schulze C, Keysers D, Breuel TM (2008) A system that learns to tag videos by watching Youtube. In: Proc of the 6th int’l conf on computer vision systems (ICVS’08). Springer, Berlin, pp 415–424

    Chapter  Google Scholar 

  86. Verge—hybrid interactive video retrieval system. http://mklab.iti.gr/verge/. Accessed 1 Dec 2011

  87. Vidi video: improving the accessibility of video. http://www.vidivideo.info. Accessed 1 Dec 2011

  88. Vitalas (video and image indexing and retrieval in the large scale): a European fp6 research project. http://vitalas.ercim.org. Accessed 1 Dec 2011

  89. Waitelonis J, Osterhoff JP, Sack H (2011) More than the sum of its parts: Contentus—a semantic multimodal search user interface. In: Proc of workshop on visual interfaces to the social and semantic Web (VISSW), co-located with ACM IUI 2011, 13 February 2011, Palo Alto, US, CEUR workshop proceedings, vol 694

  90. Waitelonis J, Sack H (2010) Exploratory semantic video search with Yovisto. In: Proc of the 4th IEEE ICSC. Pittsburgh, PA, USA

  91. Wgs84 geo positioning: an rdf vocabulary. http://www.w3.org/2003/01/geo/wgs84_pos. Accessed 1 Dec 2011

  92. Witten IH, Bainbridge D, Nichols DM (2009) How to build a digital library, 2nd edn. Morgan Kaufmann, San Francisco

    Google Scholar 

  93. Worring M, Schreiber G (2007) Semantic image and video indexing in broad domains. IEEE Trans Multimedia 9(5):909–911

    Article  Google Scholar 

  94. WS-BPEL: Web services business process execution language (specification). http://docs.oasis-open.org/wsbpel/2.0/OS/wsbpel-v2.0-OS.html. Accessed 1 Dec 2011

  95. WS-RF: Web services resource framework (primer). http://docs.oasis-open.org/wsrf/wsrf-primer-1.2-primer-cd-02.pdf. Accessed 1 Dec 2011

  96. Wu L, Hua XS, Yu N, Ma WY, Li S (2008) Flickr distance. In: Proceeding of the 16th ACM int’l conf on multimedia, MM ’08. ACM, New York, pp 31–40

    Chapter  Google Scholar 

  97. Yan R, Hauptmann AG (2007) A review of text and image retrieval approaches for broadcast news video. Inf Retr 10:445–484

    Article  Google Scholar 

  98. Zheng Y, Liu C, Ding X, Pan S (2001) Form frame line detection with directional single-connected chain. In: Proc of int conf on document analysis and recognition (ICDAR). IEEE Computer Society, Los Alamitos, pp 699–703

    Google Scholar 

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Acknowledgements

We would like to kindly thank Andreas Hess for initial input, Jan Hannemann for coordination and supporting of the review process and Klaus Bossert for review. The project contentus was funded by means of the German Federal Ministry of Economy and Technology under the promotional reference “01MQ07003”.

Our project partners are:

•    German National Library (Project lead, content provision and semantic technologies),

•    Deutsche Thomson OHG (Processing of audio/visual media),

•    Fraunhofer Institute for Intelligent Analysis and Information Systems (Text and speech processing, workflow engine),

•    Fraunhofer Heinrich Hertz Institute (Audio/visual and still image processing),

•    Hasso Plattner Institut (since 2009) (User interface, personalization),

•    Institut für Rundfunktechnik GmbH (Requirements specification, content provision),

•    Moresophy GmbH (until 2009) (User interface and semantic technologies), and

•    Mufin GmbH (Audio processing and classification).

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Nandzik, J., Litz, B., Flores-Herr, N. et al. CONTENTUS—technologies for next generation multimedia libraries. Multimed Tools Appl 63, 287–329 (2013). https://doi.org/10.1007/s11042-011-0971-2

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