Intangible heritage management and multimodal navigation

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Albano Parisi
8 anni fa
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1 Intangible heritage management and multimodal navigation R. Schettini, G. Ciocca, A. Colombo, I. Gagliardi*, MT Artese* D.I.S.Co. (Dip. Informatica, Sistemistica e Comunicazione) Università degli Studi di Milano-Bicocca, Viale Sarca 336, Milano Italy Schettini, colomboal, ciocca@disco.unimib.it * ITC, Consiglio Nazionale delle Ricerche Via Bassini 15, Milano, i.gagliardi@itc.cnr.it

Informatica, Sistemistica e Comunicazione) Università degli Studi di Milano-Bicocca, Viale Sarca

2 Intangible cultural heritage According to the 2003 Convention for the Safeguarding of the Intangible Cultural Heritage of Unesco,,the intangible cultural heritage (ICH) or living heritage is defined as the practices, representations, expressions, as well as the knowledge and skills, that communities, groups and, in some cases, individuals recognise as part of their cultural heritage. The Archive of Ethnography and Social History of the Lombardy Region (AESS) was founded to preserve, study, and enhance the value of documents and images of the life, social transformations, literature, oral history, material culture, and anthropic landscapes of the Lombard territory.

individuals recognise as part of their cultural heritage.

3 Archive of Ethnography and Social History of the Lombardy Region (AESS)

4 The archive is composed of oral documents, related to songs, 3000 textual transcriptions, 2000 musical transcriptions, 5000 audio files in MP3 format, and photographic documents, videos, The AESS Web Site

5 Information retrieval in The AESS Web Site Several retrieval Methods are implemented in the AESS site: 1. Retrieval in SQL standard, and Similarity-based textual description (not described here, please contact 2. Similarity based audio retrieval, cluster based audio retrieval (not described here, please contact 3. Image and video retrieval (this talk)

Retrieval in SQL standard, and Similarity-based textual description (not described here, please

6 Key Ideas: Image indexing and retrieval Open issues: Our solution quicklook (DEMO)

7 QuickLook 2

8 The Quicklook 2 system Overview Web-Demo at /quicklook/

9 QuickLook 2 Query Reformulation Features Weights Relevant Objects Positive Examples Negative Examples Shape Color Agreement between positive examples Agreement between positive and negative examples Query W h + Weight Estimation W h + -W h * W h * W h pianta con lunghi steli sinu pianta con lunghi steli sinuosi e larghe pianta con lunghi steli foglie (" pianta con sinu pianta con lunghi lunghi steli sinu pianta steli sinuosi e larghe con lunghi steli sinuosi e foglie ("albero della larghe foglie ("albero vita"); sul collo, ampia della vita"); sul collo fascia con motivo a albero della vita"); sul treccia; tipologia ("albero collo, ampia fascia con della vita"); motivo a treccia; tipologia pianta ("albero con della lunghi steli vita"); sinu pianta con lunghi steli sinuosi e larghe foglie ("albero della vita"); sul collo, ampia pianta con lunghi steli sinu pianta con lunghi steli sinuosi e larghe foglie ("albero della vita"); sul collo, ampia fascia con motivo a treccia; tipologia ("albero della vita"); Pictorial Textual SIMILARITY EVALUATION Ranked Results pianta con lunghi steli sinu pianta con lunghi steli sinuosi e larghe foglie ("albero della vita"); sul collo, ampia fascia con motivo a treccia; tipologia "arcaica". Dipinto in bruno di manganese e verde rame. osi e larghe foglie ("albe pianta con lunghi steli sinuosi e larghe foglie ("albero della vita"); sul collo, ampia fascia con motivo a treccia; tipologia "arcaica". Dipinto in bruno di manganese e verde rame. ro della vita"); sul collo, ampia fascia con motivo a treccia; tipologia "arcaica". Dipinto in bruno di manganese e verde rame.v pianta con lunghi steli sinuosi e larghe foglie ("albero della vita"); Database

steli sinu pianta steli sinuosi e larghe con lunghi steli sinuosi e foglie ("albero della larghe foglie ("albero vita"); sul collo, ampia della vita"); sul collo fascia con motivo a albero della

10 Quick Look 2 Retrieval Example

11 Quick Look 2 Retrieval Example

12 1 Q DR QDRK Q BRG QRG QRB Q GB ROIs Q Q DSP Hidden Layers P RJ Video indexing 1. Video segmentation 2. Video summarization 1 3. Frame Indexing and Retrieval using Quicklook Overall KF Classification Accuracy: Overall KF Classification Accuracy: 88% as Indoor 90% as Outdoor 89% as Close-up ROIs Statistics 95% as to be Retained 74% as to be Rejected Semantic Signature Fisher's Discriminant Analysis on the clustering merging costs CART Dynamic Range Over/Under-exposure Color Balance Rejected Key Frames Color Histogram Edge Direction Histogram Wavelet Statistics Complete-Link Hierarchical Clustering Maximum at 27 th summary level

Close-up ROIs Statistics 95% as to be Retained 74% as to be Rejected Semantic Signature Fisher's Discriminant Analysis on the clustering merging costs CART

13 Video indexing Unprocessed Summary (30 min MPEG-4-45,753 Frames - 55 Key Frames )

14 Video indexing The rejected Key Frames (30 min MPEG-4-45,753 Frames - 55 Key Frames )

15 Video indexing After Key Frames Removal (46 Key Frames - 9 Rejected)

16 Video indexing Key Frames Grouping Clustering (Excerpt of the first levels)

17 Video indexing Default Summary Level After Key Frames Grouping and Fisher s Analysis (Level 27 Summary - 19 Key Frames )

18 Video indexing Before and After

19 Developed Systems

20 3D Visualization Tools + = &

21 Conclusions The AESS web site is available at the address (or

22 Movies\Comp_lolalast.mpg Work in progress Video restoration Movies\CMP_LaRochelle.mpg Movies\Comp_we_BLA_SS_PS02.mpg Movies\CMP_Afrik.mpg Movies\CMP_Seq6_Br.mpg Movies\CMP_dipl.mpg

23 Content aware processing Work in progress

24 Work in progress

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