RICERCA ITALIANA     

Programmi di ricerca simili:

• 1 - Metodi basati sulla similarita' per la visione artificiale e il riconoscimento delle forme: Teoria, algoritmi, applicazioni
• 2 - Sintesi automatica di modelli astratti a partire da dati temporali o spaziali
• 3 - Metodi e strumenti per la migrazione di sistemi software verso architetture web e orientate ai servizi: valutazione sperimentale, usabilita' e trasferimento tecnologico
• 4 - SurgAid: nuovi metodi di diagnosi e supporto nella procedura chirurgica di riparazione valvolare mediante l’integrazione di modelli agli elementi finiti ed elaborazione avanzata di immagini ecocardiografiche 4D.
• 5 - Web Ram: web retrieval and mining
• 6 - Metodologie statistiche per l'analisi di impatto e la valutazione della regolamentazione
• 7 - Future applicazioni del paradigma peer-to-peer
• 8 - Tecniche avanzate per la stima e previsione degli eventi idrologici estremi ed analisi quantitativa dell'incertezza
• 9 - METODI E MODELLI STATISTICI PER LA VALUTAZIONE DEI PROCESSI FORMATIVI
• 10 - Implementazione ed ottimizzazione di un sistema ad integrazione telematica per il follow-up dei pazienti a rischio cardiovascolare.

Classificazione scientifico-disciplinare

• Area scientifico disciplinare: Scienze matematiche e informatiche
  • INFORMATICA

Classificazione brevettuale

• PHYSICS
  • COMPUTING; CALCULATING; COUNTING (score computers for games A63; combinations of writing applicances with computing devices B43K29/08)
    • IMAGE DATA PROCESSING OR GENERATION, IN GENERAL (specially adapted for particular applications, see the relevant subclasses, e.g. G06K, G09G, H04N) [N9408]

Classificazione geografica

• Regione: Veneto

Bibliografia

[AA93] Farshid Arman and J. K. Aggarwal. Model-based object recognition in dense-range images: a review. ACM Comput. Surv., 25(1):5-43, 1993.

[BCGM00] E. Berenci, C. Carpineto, V. Giannini, and S. Mizzaro. Effectiveness of keyword-based display and selection of retrieval results for interactive searches. International Journal on Digital Libraries, 3(3):249–260, October 2000. ISSN: 1432-5012.

[BET95] H. H. Bultho, S. Y. Edelman, and M. J. Tarr. How are threedimensional objects represented in the brain? Cerebral Cortex, 5(3), 1995.

[Blu67] Harry Blum. A transformation for extracting new descriptors of shape. In Proc. Models for the Perception of Speech and Visual Form, pages 362-380, November 1967.

[Bor03] Pia Borlund. The concept of relevance in IR. Journal of the American Society for Information Science and Technology, 54(10):913–925, 2003.

[BOV02] A. Barla, F. Odone, and A. Verri. Hausdor kernel for 3D object acquisition and detection. In ECCV, 2002.

[BTF04] S. Boughorbel, J. P. Tarel, and F. Fleuret. Non-mercer kernels for svm object recognition. In Proc. of British Machine Vision Conference, pages 137-146, London, UK, 2004.

[BV02] C. Buckley and E.M. Voorhees. The effect of topic set size on retrieval experiment error. In Proceedings of the 25th Annual International ACM SIGIR Conference, pages 316–323, Tampere, Finland, 2002.

[CDF+04] G. Csurka, C. Dance, L. Fan, J. Willamowsky, and C. Bray. Visual categorization with bags of keypoints. In Int. Work. On Stat. Learn. in CV, ECCV, 2004.

[CLE] CLEF Website. http://www.clef-campaign.org/.

[CROV05] A. Caponnetto, L. Rosasco, F. Odone, and A. Verri. Support Vector algorithms as Regularization Networks. In Proc. of the 13th European Symp. on Art. Neural Net., 2005.

[DAOV06] E. Delponte, E. Arnaud, F. Odone, and A. Verri. 3D object recognition with trains of keypoints. Technical Report DISI-TR-2006-07, DISI, Universita’ di Genova, 2006.

[DM06] Gianluca Demartini and Stefano Mizzaro. A classification of IR effectiveness metrics. In Advances in Information Retrieval, 28th European Conference on IR Research, ECIR 2006, LNCS 3936, pages 488–491, London, UK, 2006.

[Eng] 3D Model Similarity Search Engine. http://merkur01.inf.uni-
konstanz.de/cccc.

[EPP00] T. Evgeniou, M. Pontil, and T. Poggio. Regularization Networks and Support Vector Machines. Adv. Computat. Mathem., 13(1), 2000.

[FMK+03] T. Funkhouser, P. Min, M. Kazhdan, J. Chen, A. Halderman, and D. Dobkin. A search engine for 3d models. ACM Trans. Graph., 22:83-105, January 2003.

[FTG03] V. Ferrari, T. Tuytelaars, and L. Van Gool. Wide-baseline muliple-view correspondences. In Proceedings of CVPR, 2003.

[GB05] M. Grabner and H. Bischof. Object recognition based on local feature trajectories. In I Cognitive Vision Work., 2005.

[GZ04] Andrea Giachetti and Gianluigi Zanetti. AQUATICS reconstruction software: the design of a diagnostic tool based on computer vision algorithms. In ECCV'04 Work. CVAMIA and MMBIA, volume 3117 of LNCS, May 2004.

[HJBJ+96] A. Hoover, G. Jean-Baptiste, X. Jiang, P.J. Flynn, H. Bunke, D. Goldgof, K. Bowyer, D. Eggert, A. Fitzgibbon, and R. Fisher. An experimental comparison of range segmentation algorithms. IEEE Trans. on Pat. Anal. and Mach. Intel, 7(18):673{689, 1996.

[INE] INEX Website. http://inex.is.informatik.uni-duisburg.de/.

[IV] Ogden IV. http://www.nime.ac.jp/motofumi/ogden.

[IJ05] P. Ingwersen and K. Jarvelin. The Turn—Integration of Information Seeking and Retrieval in Context. Springer, 2005.

[JMF99] A. K. Jain, M. N. Murty, and P. J. Flynn. Data clustering: a review. ACM Comput. Surv., 31(3):264{323, 1999.

[KS98] H.P. Kriegel and T. Seidl. Approximation-based similarity search for 3d surface segments. GeoInformatica Journal, 2:113-147, 2 1998.

[KT03] Sagi Katz and Ayellet Tal. Hierarchical mesh decomposition using fuzzy clustering and cuts. ACM Trans. Graph., 22(3):954-961, July 2003.

[LIMA3D] Sistema automatico di acquisizione e modellazione 3D a basso costo. Progetto PRIN 2003. Protocollo 2003011918.

[Miz97] S. Mizzaro. Relevance: The whole history. Journal of the American Society for Information Science, 48(9):810–832, September 1997.

[MN95] H. Murase and S. H. Nayar. Visual learning and recognition of 3-d objects from appearence. IJCV, 14:5-24, January 1995.

[NK03] M. Novotni and R. Klein. 3d zernike descriptors for content based shape retrieval. In Solid Modeling 2003, 2003.

[NTC] NTCIR Website. http://research.nii.ac.jp/ntcir/.

[OFCD02] R. Osada, T. Funkhouser, B. Chazelle, and D. Dobkin. Shape distributions. ACM Trans. Graph., 21:807BV{832, April 2002.

[OV06] F. Odone and A. Verri. Image classi¯cation and retrieval with kernel methods. In G. Camps-Valls, editor, Kernel methods in bioengineering, communications, and image processing. Idea Group, 2006. In press.

[PDDM06] P.Daras, D.Zarpalas, D.Tzovaras, and M.G.Strintzis. Efficient 3-d model search and retrieval using generalized 3-d radon transforms. IEEE Trans. Multim., 8(1):101-114, 2006.

[Pet02] Sylvain Petitjean. A survey of methods for recovering quadrics in triangle meshes. ACM Comput. Surv., 34(2):211-262, 2002.

[PV98] M. Pontil and A. Verri. Support vector machines for 3d object recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence, 6:637-646, 1998.

[Ret] 3D Shape Retrieval. http://www.cs.uu.nl/centers/3dmatching.html.

[SMD+05] Ali Shokoufandeh, Diego Macrini, Sven Dickinson, Kaleem Siddiqi, and Steven W. Zucker. Indexing hierarchical structures using graph spectra. PAMI, 27(7):1125{1140, July 2005.

[SSGD03] H. Sundar, D. Silver, N. Gagvani, and S. Dickinson. Skeleton based shape matching and retrieval. In SMI, pages 130-139, 2003.

[STC04] J. Shawe-Taylor and N. Cristianini. Kernel methods for pattern analysis. Cambridge University Press, 2004.

[SW02] Robert J.T. Sadleir and Paul F. Whelan. Colon centreline calculation for ct colonography using optimised 3D topological thinning. In 3DPVT'02, pages 800{803, June 2002.

[Sys] 3D Model Retrieval System. http://3d.csie.ntu.edu.tw/dynamic.

[TG00] T. Tuytelaars and L. Van Gool. Wide baseline stereo matching based on local, affine invariant regions. In Proceedings of BMVC, pages 412-425, 2000.

[TRE] TREC Video Track. http://www-nlpir.nist.gov/projects/trecvid/.

[TV04] Johan W. H. Tangelder and Remco C. Veltkamp. A survey of content based 3d shape retrieval methods. In Proc. SMI, pages 145-156, 2004.

[Vap98] V. Vapnik. Statistical learning theory. John Wiley and sons, New York, 1998.

[VBK01] Remco C. Veltkamp, Hans Burkhardt, and Hans-Peter Kriegel, editors. State-of-the-Art in Content-Based Image and Video Retrieval. Kluwer, 2001.

[VCD02] J.-Ph. Vandeborre, V. Couillet, and M. Daoudi. A practical approach for 3d model indexing by combining local and global invariants. In 3DPVT'02, 2002.

[VH05] M. Ellen Voorhees and Donna K. Harman, editors. TREC—Experiment and Evaluation in Information Retrieval. MIT Press, September 2005.

[VSR01] D. V. Vranic, D. Saupe, and J. Richter. Tools for 3d-object retrieval: Karhunen-loeve-transform and spherical harmomics. In Proc. IEEE MMSP'01, 2001.

[WCG03] C. Wallraven, B. Caputo, and A. Graf. Recognition with local features: the kernel recipe. In ICCV, page 257, 2003.

[ZP04] T. Zaharia and F. Preteux. 3d versus 2d/3d shape descriptors: A comparative study. In Proc. SPIE Conference on Image Processing: Algorithms and Systems III - IS&T / SPIE Symposium on Electronic Imaging, Science and Technology '04, San Jose, CA, volume 5298, pages 47{58, January 2004.

[ZSM+05] Juan Zhang, Kaleem Siddiqi, Diego Macrini, Ali Shokoufandeh, and Sven J. Dickinson. Retrieving articulated 3-d models using medial surfaces and their graph spectra. In EMMCVPR, pages 285-300, 2005.

[ZT99] Yong Zhou and Arthur W. Toga. Effcient skeletonization of volumetric objects. IEEE TVCG, 5(3):196-209, July – September 1999.

Parole Chiave

VISIONE COMPUTAZIONALE, GRAFICA COMPUTAZIONALE, REPERIMENTO DELLE INFORMAZIONI, APPRENDIMENTO STATISTICO, RICERCA PER CONTENUTO 3D, REPERIMENTO DI FORME 3D, DESCRITTORI DI FORME 3D, CARATTERISTICHE LOCALI, VALUTAZIONE SPERIMENTALE