Semantic force relevance feedback, content-free 3D object retrieval and annotation propagation: Bridging the gap and beyond

Multimedia Tools and Applications

Volumn 39, Issue 2, 2008, Pages 217-241

  Onasoglou, Efstathios ^a   Daras, Petros ^a  

^a INFORMATION TECHNOLOGIES INSTITUTE   (Greece)

Author keywords

Clustering; Relevance feedback; Semantic propagation

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; CONTROL THEORY; CRACK PROPAGATION; EVOLUTIONARY ALGORITHMS; FEEDBACK; FEES AND CHARGES; FINANCE; GALLIUM ALLOYS; INFORMATION THEORY; MULTIMEDIA SYSTEMS; SCHEDULING ALGORITHMS; SEMANTICS;

3 D OBJECTS; 3D OBJECT RETRIEVAL; ANNOTATION PROPAGATION; BUSINESS MEDIA; DESCRIPTORS; FEATURE SPACES; FEATURE VECTOR (FV); HIGH LEVEL FEATURES; LINEAR PREDICTION (LP); MULTIMEDIA DATABASE SYSTEMS; NOVEL ALGORITHMS; OBJECT DATABASES; RELEVANCE FEEDBACK (RRF); RETRIEVAL (MIR); RETRIEVAL ACCURACY; RETRIEVAL METHODS; SEMANTIC GAPS; SPRINGER (CO);

DATABASE SYSTEMS;

EID: 46749133455     PISSN: 13807501     EISSN: 15737721     Source Type: Journal    
DOI: 10.1007/s11042-008-0216-1     Document Type: Article

References (35)

1. Atmosukarto I, Leow WK, Huang Z (2005) Feature combination and relevance feedback for 3d model retrieval. In: Proc. of the 11th int. conf. multimedia modelling. IEEE Computer Society, Washington, DC, pp 334-339
2. Bang HY, Chen T (2002) Feature space warping: an approach to relevance feedback. In: IEEE int. conf. on image processing. Rochester, 22-25 September 2002, pp 968-971
3. Barnard JM, Willett P, Downs GM (1998) Chemical similarity searching. J Chem Inf Comput Sci 38(6):983-996
4. Blachnik M, Duch W, Wieczorek T (2005) Probabilistic distance measures for prototype-based rules. In: Proc. of the 12th int. conf. on neural information processing. Taipei University Press, Taiwan, 30 October-2 November 2005, pp 445-450
5. Chan LW, Chiang CC, Hung YP (2005) Content-based object movie retrieval by use of relevance feedback. In: Proc. int. conf. on image and video retrieval. Singapore, July 2005, pp 425-434
6. Chen SC, Hunag X, Shyu ML (2003) Incorporating real-valued multiple instance learning into relevance feedback for image retrieval. IEEE Int Conf Multimed Expo 2:321-324
7. Chen T, Liu D (2005) Probabilistic relevance feedback with binary semantic feature vectors. In: IEEE proc. int. conf. acoustics, speech and signal processing. Philadelphia, 18-23 March 2005
8. Cox IJ, Miller ML, Omohundro SM, Yianilos PN (1996) Pichunter: Bayesian relevance feedback for image retrieval. In: Proc. of the int. conf. on pattern recognition. IEEE Computer Society, Washington, DC, p 361
9. Daras P, Zarpalas D, Tzovaras D, Strintzis MG (2006) Efficient 3-d model search and retrieval using generalized 3-d radon transforms. IEEE Trans Multimedia 8(1):101-114
10. Flickner M, Sawhney H, Niblack W, Ashley J, Huang Q, Dom B, Gorkani M, Hafner J, Lee D, Petkovic D, Steele D, Yanker P (1995) Query by image and video content: the qbic system. Computer 28(9):23-32
11. He X, Ma WY, King O, Li M, Zhang H (2002) Learning and inferring a semantic space from user's relevance feedback for image retrieval. In: Proc. of the tenth ACM int. conf. on multimedia. Juan les Pins, 1-6 December 2002, pp 343-346
12. Huang TS, Chen Y, Zhou X (2001) One-class svm for learning in image retrieval. In: IEEE int. conf. on image processing. IEEE, Piscataway, pp 34-37
13. Ishikawa Y, Subramanya R, Faloutsos C (1998) MindReader: querying databases through multiple examples. In: Proc. 24th int. conf. very large data bases. New York, 24-27 August 1998, pp 218-227
14. Kanade T, Uchihashi S (2004) User-powered content-free approach to image retrieval. In: Proc. of int. symposium on digital libraries and knowledge communities in networked information society. Tsukuba, March, pp 24-32
15. Kazhdan M, Funkhouser T, Rusinkiewicz S (2003) Rotation invariant spherical harmonic representation of 3d shape descriptors. In: Proc. of the 2003 eurographics/ACM SIGGRAPH symposium on geometry processing. Eurographics Association. Aire-la-Ville, pp 156-164
16. Leifman G, Meir R, Tal A (2005) Semantic-oriented 3d shape retrieval using relevance feedback. Vis Comput 21(8-10):865-875
17. Liu D, Chen T (2006) Content-free image retrieval using bayesian product rule. In: IEEE int. conf. on multimedia and expo. IEEE, Piscataway, pp 89-92
18. Ljung L (1987) System identification: theory for the user. Prentice-Hall, New York
19. Milanfar P, Farsiu TH (2007) Kernel regression for image processing and reconstruction. IEEE Trans Image Process 16(2):349-366
20. Neskovic P, Wang J, Cooper LN (2007) Bayes classification based on minimum bounding spheres. Neurocomput 70(4-6):801-808
21. Oh S, Gyo Chung M, Sull S (2004) Relevance feedback reinforced with semantics accumulation. In: Int. conf. on image and video retrieval. Dublin, 21-23 July 2004, pp 448-454
22. Rui Y, Huang TS, Mehrotra S (1998) Relevance feedback techniques in interactive content-based image retrieval. In: Storage and retrieval for image and video databases. San Jose, 28-30 January 1998, pp 25-36
23. Sayood K (2003) Introduction to data compression. Morgan Kaufman, San Mateo
24. Schölkopf B, Smola A, Müller KR (1998) Nonlinear component analysis as a kernel eigenvalue problem. In: Neural computation, vol. 10. MIT, Cambridge, pp 1299-1319
25. Shilane P, Min P, Kazhdan MM, Funkhouser TA (2004) The princeton shape benchmark. In: Int. conf. on shape modeling and applications. IEEE Computer Society, Piscataway, pp 167-178
26. Stork D, Duda R, Hart P (2000) Pattern classification, 2nd edn. Wiley-Interscience, New York
27. Su Z, Zhang HJ, Li S, Ma S (2003) Relevance feedback in content-based image retrieval: Bayesian framework, feature subspaces, and progressive learning. IEEE Trans Image Process 12(8):924-937
28. Tian Q, Hong P, Huang TS (2000) Update relevant image weights for content-based image retrieval using support vector machines. In: Int. conf. on multimedia and expo. IEEE, Piscataway, pp 1199-1202
29. Tong S, Chang E (2001) Support vector machine active learning for image retrieval. In: ACM Multimedia. ACM, New York, pp 107-118
30. Tsang V, Stevenson S (2004) Calculating semantic distance between word sense probability distributions. In: Proc. of conf. on computational natural language learning. Boston, May 2004, pp 81-88
31. Vapnik VN (1998) Statistical learning theory. Wiley-Interscience, New York
32. Wang J, Neskovic P, Cooper LN (2006) A minimum sphere covering approach to pattern classification. In: Int. conf. of pattern recognition. Hong Kong, 20-24 August 2006, pp 433-436
33. Zitnick C (2003) Computing conditional probabilities in large domains by maximizing Renyi's quadratic entropy. Ph.D. thesis, Robotics Institute, Carnegie Mellon University, May
34. Zhang C, Chen T (2002) An active learning framework for content-based information retrieval. IEEE Trans Multimedia 4(2):260-268
35. Zhang HJ, Su Z (2001) Improving cbir by semantic propagation and cross modality query expansion. In: Proc. of the int. workshop on multimedia content-based indexing and retrieval. Brescia, 19-21 September 2001, pp 83-86