Distributed Multimedia Database Technologies Supported by MPEG-7 and MPEG-21

1. Lu, G., Multimedia Database Management Systems, Artech House, 1999.

2. Subrahmanian, V.S., Principles of Multimedia Database Systems, Morgan Kaufman Press, 1998.

3. Ono, A., Amano, M., and Hakaridani, M., A flexible content-based image retrieval system with combined scene description keywords, in Proceedings of the IEEE Conference on Multimedia Computing and Systems, Hiroshima, Japan, June 1996, pp. 201–208.

4. Sebe, N. and Lew, M.S., Color-based retrieval, Pattern Recog. Lett., 22, 223–230, 2001.

5. Deng, Y., Manjunath, B.S., Kenney, C., Moore, M.S., and Shin, H., An efficient color representation for image retrieval, IEEE Trans. Image Process., 10, 140–147, 2001.

6. Adjeroh, D.A. and Lee, M.C., On ratio-based color indexing, IEEE Trans. Image Process., 10, 36–48, 2001.

7. Berens, J., Finlayson, G.D., and Qiu, G., Image indexing using compressed colour histograms, IEEE Vision Image Signal Process., 147, 349–355, 2000.

8. Chahir, Y. and Chen, L., Searching images on the basis of color homogeneous objects and their spatial relationship, J. Visual Comm. Image Representation, 11, 302–326, 2000.

9. Syeda-Mahmood, T. and Petkovic, D., On describing color and shape information in images, Signal Process. Image Comm., 16, 15–31, 2000.

10. Berretti, S., del Bimbo, A., and Pala, P., Indexed retrieval by shape appearance, IEEE Vision Image Signal Process., 147, 356–362, 2000.

11. Huet, B. and Hancock, E.R., Shape recognition from large image libraries by inexact graph matching, Pattern Recogn. Lett., 20, 1259–1269, 1999.

12. Wu, P., Manjunath, B.S., Newsam, S.D., and Shin, H.D., A texture descriptor for browsing and similarity retrieval, Signal Process. Image Comm. , 16, 33–43, 2000.

13. Tao, B. and Dickinson, B.W., Texture recognition and image retrieval using gradient indexing, J. Visual Comm. Image Representation, 11, 327–342, 2000.

14. Zhong, D., Kumar, R., and Chang, S.-F., Personalized video: real-time personalized sports video filtering and summarization, in Proc. of ACM Multimedia 2001, AMC Press, Ottowa, 2001, pp. 623–625.

15. Snoek, C.G.M. and Worring, M., Multimodal Video Indexing: A Review of the State-of-the-Art. Multimedia Tools and Applications, to appear; also available as ISIS TR, Vol. 2001-20, December 2001.

16. Zhang, T. and Kuo, C.C. Jay, Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing, Kluwer, Dordrecht.

17. Hampapur, A., Semantic video indexing: approach and issues, ACM Sigmod Rec., 28, 32–39, 1999.

18. Lee, M.S., Yang, Y.M., and Lee, S.W., Automatic video parsing using shot boundary detection and camera operation analysis, Pattern Recog., 34, 711–719, 2001.

19. Dimitrova, N., McGee, T., and Elenbaas, H., Video keyframe extraction and filtering: a keyframe is not a keyframe to everyone, in Proceedings of the 6th International Conference on Information and Knowledge Management (CIKM-97), Las Vegas, NV, November 1997, ACM Press, pp. 113–120.

20. Dufaux, F., Key frame selection to represent a video, in Proceedings of the IEEE International Conference on Image Processing, Vancouver, Canada, September 2000.

21. Zhang, H.J., Kankanhalli, A., and Smoliar, S.W., Automatic partitioning of full-motion video, ACM Multimedia Syst., 1, 10–28, 1993.

22. Boreczsky, J.S. and Rowe, L.A., A comparison of video shot boundary detection techniques, J. Electron. Imaging, 5, 122–128, 1996.

23. Ahanger, G. and Little, T.D.C., A survey of technologies for parsing and indexing digital video, J. Visual Comm. Image Representation, 7, 28–43, 1996.

24. Patel, N.V. and Sethi, I., Video segmentation for video data management, in The Handbook of Multimedia Information Management, Grosky, W.I., Jain, R., and Mehrotra, R., Eds., Prentice-Hall, Englewood Cliffs, NJ, 1997.

25. Yu, H.H. and Wolf, W., A hierarchical multiresolution video shot transition detection scheme, Comp. Vision Image Understanding, 75, 196–213, 1999.

26. Kosch, H., Tusch, R., Böszörményi, L., Bachlechner, A., Dörflinger, B., Hofbauer, C., Riedler, C., Lang, M., and Hanin, C., SMOOTH—a distributed multimedia database system, in Proceedings of the International VLDB Conference, Rome, Italy, September 2001, pp. 713–714.

27. Schonfeld, D. and Lelescu, D., Vortex: video retrieval and tracking from compressed multimedia databases—multiple object tracking from MPEG-2 bit stream, J. Visual Comm. Image Representation, 11, 154–182, 2000.

28. Milanese, R., Deguillaume, F., and Jacot-Descombes, A., Efficient segmentation and camera motion indexing of compressed video, Real-Time Imaging, 5, 231–241, 1999.

29. Rui, Y., Huang, T.S., and Mehrotra, S., Exploring video structure beyond the shots, in Proceedings of the IEEE International Conference on Multimedia Computing and Systems, Austin, Texas, June 1998, pp. 237–240.

30. Toklu, C., Liou, S.P., and Das, M., Video abstract: a hybrid approach to generate semantically meaningful video summaries, in Proceedings of the IEEE International Conference on Multimedia and Exposition, New York, July 2000, pp. 57–61.

31. Manske, K., Mühlhäuser, M., Vogel, S., and Goldberg, M., OBVI: hierarchical 3D video-browsing, in Proceedings of the 6th ACM International Conference on Multimedia (Multimedia-98), New York, September 1998, ACM Press, pp. 369–374.

32. Sawhney, H., Ayer, A., and Gorkani, M., Model based 2D and 3D dominant motion estimation for mosaicing and video representation, in Proceedings of the International Conference on Computer Vision, Cambridge, MA, 1995, IEEE CS Press, pp. 583–590.

33. Tzanetakis, G. and Cook, P., Multifeature audio segmentation for browsing and annotation, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, New York, October 1999.

34. Rossignol, S., Rodet, X., Soumagne, J., Collette, J.-L., and Depalle, P., Feature extraction and temporal segmentation of acoustic signals, in Proceedings of the International ICMC: International Computer Music Conference, Ann Arbor, MI, October 1998.

35. Eren, P.E. and Tekal, A.M., Keyframe-based bi-directional 2-d mesh representation for video object tracking and manipulation, in Proceedings of the IEEE International Conference on Image Processing, Kobe, Japan, 1999, IEEE CS Press, pp. 968–972.

36. Eng, H.L. and Ma, K.K., Spatio-temporal segmentation of moving video objects over mpeg compressed domain, in Proceedings of the IEEE International Conference on Multimedia and Exposition, New York, July 2000, pp. 1531–1534.

37. Jang, D.S., Kim, G.Y., and Choi, H.I., Model-based tracking of moving object, Pattern Recog., 30, 999–1008, 1997.

38. Carson, C. et al., Blobworld: image segmentation using expectation-maximization and its application to image querying, IEEE Trans. Pattern Anal. Machine Intell., 24, 1026–1038, 2002.

39. Chang, Y.L., Kamel, W., and Alfonso, R., Integrated image and speech analysis for content-based video indexing, in Proceedings of the 3rd IEEE International Conference on Multimedia Computing and Systems, Hiroshima, Japan, 1996, pp. 306–313.

40. Assfalg, J., Bertini, M., Colombo, C., and Del Bimbo, A., Semantic characterization of visual content for sports videos annotation, in Proc. of Multimedia Databases and Image Communication, Amalfi, September 2001, Springer-Verlag, Heidelberg, LNCS 2184, pp. 179–191.

41. Okada, K. and von der Malsburg, C., Automatic video indexing with incremental gallery creation: integration of recognition and knowledge acquisition, in Proceedings of the Third International Conference on Knowledge-Based Intelligent Information Engineering Systems, Adelaide, August 31, 1999, pp. 431–434.

42. Ide, I., Yamamoto, K., and Tanaka, H., Automatic video indexing based on shot classification, in Proceedings of the International Conference on Advanced Multimedia Content Processing, Osaka, 1999, Springer-Verlag, Heidelberg, LNCS 1554, pp. 87–102.

43. Correia, P. and Pereira, F., The role of analysis in content based video coding and indexing, Signal Process., 66, 125–142, 1998.

44. Chen, S.-C., Kashyap, R.L., and Ghafoor, A., Semantic Models for Multimedia Database Searching and Browsing, Kluwer, Dordrecht, 2000.

45. Smith, J. and Chang, S.F., Visually searching the web for content, IEEE MultiMedia, 4, 12–20, 1997.

46. Jorgensen, C., Jaimes, A., Benitez, A.B., and Chang, S.-F., A conceptual framework and research for classifying visual descriptors, J. Am. Soc. Info. Sci., 52(11), 938–947, 2001.

47. Benitez, B., Chang, S.-F., and Smith, J.R., IMKA: a multimedia organization system combining perceptual and semantic knowledge, Proceeding of the 9th ACM International Conference on Multimedia (ACM MM-2001), Ottawa, September 30–October 5, 2001, pp. 630–631.

48. Zhong, D. and Chang, S.-F., Structure analysis of sports video using domain models, IEEE Conference on Multimedia and Exhibition, Tokyo, August 22–25, 2001.

49. Rehm, E., Representing Internet streaming media with MPEG-7, in Proceedings of the ACM Multimedia 2000 Workshop Standards, Interoperability and Practice: Who Needs Standards Anyway?, New York, November 4, 2000, ACMPress, pp. 93–106.

50. Forsyth, D. and Fleck, M., Automatic detection of human nudes, Int. J. Comput. Vision, 32, 63–77, 1999.

51. Wang et al., Automatic linguistic indexing of pictures by a statistical modeling approach, IEEE Trans. Pattern Anal. Machine Intelligence, 25(10), 14–20, 2003.

52. Minka, T.P. and Picard, R.W., Interactive learning using a "Society of Models," Pattern Recognition, 30, 1997.

53. Roussopoulos, N., Kelley, S., and Vincent, F., Nearest neighbor queries, in Proceedings of ACM-SIGMOD Conference on Management of Data, San Jose, June 1995, pp. 71–79.

54. Berchtold, S., Bohm, C., Keim, D.A., and Kriegel, H.P., A cost model for nearest neighbor search in high-dimensional data space, in Proceedings of the ACM PODS Conference, Tucson, May 1997, pp. 78–86.

55. Pramanik, S., Alexander, S., and Li, J., An efficient searching algorithm for approximate nearest neighbor queries in high dimensions, in IEEE International Conference on Multimedia Computing and Systems, Vol. 1, Florence, Italy, June 1999, pp. 865–869.

56. Li, J.Z., Özsu, M.T., Szafron, D., and Oria, V., MOQL: a multimedia object query language, in 3rd International Workshop on Multimedia Information Systems, Como, September 1997, Springer-Verlag, Heidelberg, LNCS Series, pp. 19–28.

57. Excalibur Image DataBlade Module User's Guide, Version 1.2, Informix Press, 1999.

58. Oracle9i interMedia Audio, Image, and Video User's Guide and Reference, http://technet.oracle.com.

59. Evangelidis, G., Lomet, D., and Salzberg, B., The hB tree: a multi-attribute index supporting concurrency, recovery and node consolidation. VLDB J., 6, 1–25, 1997.

60. Ciaccia, P., Patella, M., and Zezula, P., M-Tree: an efficient access method for similarity search in metric spaces, in Proceedings of the VLDB Conference, Athens, August 1997, pp. 426–435.

61. Chakrabarti, K. and Mehrotra, S., The hybrid tree: an index structure for high dimensional feature spaces, in Proceedings of the International Conference on Data Engineering (ICDE), Sydney, March 1999, pp. 440–447.

62. Cha, G.-H. and Chung, C.-W., The GC-Tree: a high-dimensional index structure for similarity search in image databases, IEEE Trans. Multimedia, 4, 235–247, 2002.

63. Tao, Y., Papadias, D., and Shen, Q., Continuous nearest neighbor search. International Conference on VLDB 2002, Hong Kong, August 2002, pp. 287–298.

64. White, D.A. and Jain, R., Similarity indexing with the SS-tree, in Proceedings of the 12th IEEE Intl. Conference on Data Engineering, New Orleans, February 1996, pp. 516–523.

65. Kurniawati, R., Jin, J.S., and Shepherd, J.A., The SS+-tree: an improved index structure for similarity searches in a high-dimensional feature space, in Proceedings of the SPIE storage and Retrieval of Image and Video Databases, San Jose, February 1997, pp. 110–120.

66. Cha, G.-H., Zhu, X., Petkovic, D., and Chung, C.-W., An efficient indexing method for nearest neighbor searches in high-dimensional image databases, IEEE Trans. Multimedia, 4, 76–87, 2002.

67. Guttman, A., R-trees: a dynamic index structure for spatial searching, in Proceedings of ACM SIGMOD Conference of Management of Data, Boston, June 1984, pp. 47–57.

68. Berchtold, S., Keim, D.A., and Kriegel, H.-P., The X-tree: an indexing structure for high-dimensional data, in Proceedings of the VLDB Conference, Bombay, September 1996, pp. 28–39.

69. Lin, E.T., Omiecinski, E.R., and Yalamanchili, S., Large join optimization on a hypercube multiprocessor. IEEE Trans. Knowl. Data Eng., 6(2), 304–315, 1994.

70. Robinson, J.T., The K-D-B tree: a search structure for large multidimensional dynamic indexes, in Proceedings of ACM-SIGMOD International Conference on Management of Data, April 1981, pp. 10–18.

71. Wang, W., Yang, J., and Muntz, R.R., PK-tree: a spatial index structure for high dimensional point data. Technical Report 980032, Computer Science Department, University of California, Los Angeles, September 22, 1998.

72. Kim, B. and Um, K., 2d+ string: a spatial metadata to reason topological and directional relationships, in Proceedings of the 11th International Conference on Scientific and Statistical Database Management, Cleveland, July 1999, IEEE CS Press, pp. 112–121.

73. Goh, S.-T. and Tan, K.-L., MOSAIC: a fast multi-feature image retrieval system. Data Knowl. Eng., 33, 219–239, 2000.

74. Guntzer, U., Balke, W.-T., and Kiesling, W., Optimizing multi-feature queries for image databases, in Proceedings of the International Conference on Very Large Databases, Cairo, September 2000, pp. 419–428.

75. Weber, R., Schek, H.-J., and Blott, S., A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces, International Conference on VLDB 1998, New York, August 1998, pp. 194–205.

76. Gibbs, S. Breiteneder, C., and Tsichritzis, D., Data modeling of time-based media, in Proceedings of the ACM SIGMOD International Conference on Management of Data, Minneapolis, May 1994, Snodgrass, R.T., and Winslett, M., eds., Vol. 23, pp. 91–102.

77. Hjelsvold, R. and Midtstraum, R., Databases for video information sharing, in IS&T/SPIE's Symposium on Electronic Imaging Science and Technology, 1994, pp. 268–279.

78. Gross, M.H., Koch, R., Lippert, L., and Dreger, A., Multiscale image texture analysis in wavelet spaces, in Proceedings of the IEEE International Conference on Image Processing, 1994.

79. Weiss, R., Duda, A., and Gifford, D.K., Content-based access to algebraic video, in Proceedings of the International Conference on Multimedia Computing and Systems, Boston, May 1994, pp. 140–151.

80. Smith, T.G.A. and Davenport, G., The stratification system: a design environment for random access video, in Proceedings of the 3rd International Workshop on Network and Operating System Support for Digital Audio and Video, 1992.

81. Weiss, R., Duda, A., and Gifford, D.K., Composition and search with a video algebra, IEEE MultiMedia, 2, 12–25, 1995.

82. Zhong, D. and Chang, S.-F., Video object model and segmentation for content-based video indexing, in IEEE International Symposium on Circuits and Systems (ISCAS'97), Hong-Kong, June 1997.

83. Jiang, H., Montesi, D., and Elmagarmid, A.K., Integrated video and text for contentbased access to video databases, Multimedia Tools Appl., 9, 227–249, 1999.

84. Jiang, H. and Elmagarmid, A.K., Spatial and temporal content-based access to hypervideo databases, VLDB J., 7, 226–238, 1998.

85. Jiang, H. and Elmagarmid, A.K., WVTDB—a semantic content-based videotext database system on the World Wide Web, IEEE Trans. Knowl. Data Eng., 10, 947–966, 1998.

86. Bertino, E., Catania, B., and Ferrari, E., Multimedia IR: models and languages, in Modern Information Retrieval, Baeza-Yates, R. and Ribeiro-Neto, B., Eds., Addison-Wesley, Reading, MA, 1999.

87. Tusch, R., Kosch, H., and Böszörményi, L., VideX: an integrated generic video indexing approach, in Proceedings of the ACM Multimedia Conference, Los Angeles, October–November 2000, pp. 448–451.

88. Little, T.D.C., Ahanger, G., Folz, R.J., Gibbon, J.F., Reeve, F.W., Schelleng, D.H., and Venkatesh, D., A digital on-demand video service supporting content-based queries, in Proceedings of 1st ACM International Conference on Multimedia, 1993, pp. 427–436.

89. Hjelsvold, R. Midtstraum, R., and Sandstå, O. Multimedia Database Systems: Design and Implementation Strategies, Kluwer, Dordrecht, 1996, pp. 89–122.

90. Kosch, H., Slota, R., Böszörményi, L., Kitowski, J., and Otfinowski, J., An information system for long-distance cooperation in medicine, in Proceedings of the 5th International Workshop on Applied Parallel Computing, New Paradigms for HPC in Industry and Academia (PARA), Bergen, Norway, June 2000. Springer-Verlag, Heidelberg, LNCS 1947, pp. 233–241.

91. Kosch, H., Tusch, R., Böszörményi, L., Bachlechner, A., Dörflinger, B., Hofbauer, C., and Riedler, C., The SMOOTH Video DB—demonstration of an integrated generic indexing approach, in Proceedings of the ACM Multimedia Conference, Los Angeles, October–November 2000, pp. 495–496.

92. Martínez, J.M. Overview of the MPEG-7 Standard. ISO/IEC JTC1/SC29/WG11 N4980, (Klagenfurt Meeting), July 2002, http://www.chiariglione.org/mpeg/.

93. Melton, J. and Eisenberg, A., SQL multimedia and application packages (SQL/MM), SIGMOD Rec., 30(4), 97–102, 2001.

94. Information technology—Database languages—SQL Multimedia and Application Packages—Part 5: Still Image, ISO/IEC FCD 13249-5, 2003(E), December 2002.

95. Melton, J. and Eisenberg, A., SQL: 1999, formerly known as SQL3, SIGMOD Rec., 28(1), 131–138, 1999.

96. Harold, E.R. and Means, W.S., XML in a Nutshell, 2nd ed., O'Reilly and Associates, 2002.

97. Kosch, H., MPEG-7 and Multimedia Database Systems, SIGMOD Rec., 31(2), 34–39, 2002.

98. Hacid, M.-S., Decleir, C., and Kouloumdjian, J., A database approach for modeling and querying video data, IEEE Trans. Knowl. Data Eng., 12, 729–750, 2000.

99. Bonifati, A., Comparative analysis of five XML query languages, SIGMOD Rec., 29(1), 68–79, 2000.

100. Heuer, J., Casas, J.L., and Kaup, A., Adaptive multimedia messaging based on MPEG-7—the M3 box, in Proceedings of the Second International Symposium on Mobile Multimedia Systems & Applications, Delft, November 2000.

101. Kofler, A., Evaluation of Storage Strategies for XML Based MPEG-7 Data. Master's thesis, Institute of Information Technology, University Klagenfurt, 2001.

102. Amato, G., Mainetto, G., and Savino, P., An approach to a content-based retrieval of multimedia data, Multimedia Tools Appl., 7, 9–36, 1998.

103. Rui, Y., Huang, T.S., and Chang, S.-F., Image retrieval: past, present and future. J. Visua Comm. Image Representation, 10, 1–23, 1999.

104. Yoshitaka, A. and Ichikawa, T., A survey on content-based retrieval for multimedia databases, IEEE Trans. Knowl. Data Eng., 11, 81–93, 1999.

105. Apers, P.M.G. and Kersten, M.L., Content-based retrieval in multimedia databases based on feature models, in Proceedings of the International Conference on Advanced Multimedia Content Processing, Osaka, Japan, November 1998, Springer-Verlag, Heidelberg, LNCS 1554, pp. 119–130.

106. Apers, P.M.G., Blanken, H.M., and Houtsma, M.A.W., Multimedia Databases in Perspective. Springer-Verlag, Heidelberg, 1997.

107. Smith, J. and Chang, S.-F., VisualSEEk: a fully automated content-based image query system, in Proceedings of the Fourth ACM Multimedia Conference (MULTIMEDIA'96), New York, November 1996, ACM Press, pp. 87–98.

108. Flickner, M., Sawhney, H., Niblack, W., Ashley, J., Huang, Q., Dom, B., Gorkani, M., Hafner, J., Lee, D., Petkovic, D., Steele, D., and Yanker, P., Query by image and video content: the QBIC system. IEEE Comput., 28, 23–32, 1995.

109. Das, M., Riseman, E.M., and Draper, B.A., FOCUS: searching for multi-colored objects in a diverse image database, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1997, pp. 756–761.

110. Shanbehazadeh, J., Moghadam, A.M.E., and Mahmoudi, F., Image indexing and retrieval techniques: past, present, and next, in Proceedings of SPIE: Storage and Retrieval for Media Databases 2000, Yeung, M.M., Yeo, B.-L., and Bouman, C.A., eds., Vol. 3972, 2000, pp. 461–470.

111. Kelly, P.M. and Cannon, T.M., Query by image example: the CANDID approach, in Proceedings of SPIE: Storage and Retrieval for Media Databases 1995, 1995, pp. 238–248.

112. Ortega, M., Rui, Y., Chakrabarti, K., Porekaew, K., Mehrotra, S., and Huang, T.S., Supporting ranked Boolean similarity queries in MARS, IEEE Trans. Knowl. Data Eng., 10, 905–925, 1998.

113. Chang, S.-F., Chen, W., Meng, H., Sundaram, H., and Zhong, D., VideoQ: an automated content-based video search system using visual cues, in Proceedings of the 5th ACM International Multimedia Conference (MULTIMEDIA '97), New York/Reading, November 1998. ACM Press/Addison-Wesley, pp. 313–324.

114. Bach, J.R., The VIRAGE image search engine: an open framework for image management, in Proceedings of SPIE-96, 4th Conference on Storage and Retrieval for Still Image and Video Databases, San Jose, 1996, pp. 76–87.

115. Beigi, M., Benitez, A.B., and Chang, S.-F., Metaseek: a content-based metasearch engine for images, in Proceedings of the International Conference of Storage and Retrieval for Image and Video Databases (SPIE), 1998, pp. 118–128.

116. Venters, C.C. and Cooper, M., A review of content-based image retrieval systems. Technical Report JTAP-054, JISC Technology Applications Programme (JTAP) at University Manchester, Manchester, 1999.

117. Veltkamp, R.C. and Tanase, M., Content-based image retrieval systems: a survey Technical Report UU-CS-2000-34, Utrecht University, Utrecht, March 2001.

118. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., and Jain, R., Content based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Machine Intell., 22, 1349–1380, 2000.

119. Ghias, A., Logan, J., Chamberlain, D., and Smith, B.C., Query by humming-musical information retrieval in an audio database, in Proceedings of the ACM Multimedia, San Francisco, 1995, pp. 231–236.

120. Crysandt, H. and Wellhausen, J., Music classification with MPEG-7, Proceedings of the SPIE International Conference on Electronic Imaging—Storage and Retrieval for Media Databases, Santa Clara, January 2003.

121. Foote, J., An overview of audio information retrieval, ACM Multimedia Syst., 7, 2–10, 1999.

122. Foote, J.T., Multimedia Storage and Archiving Systems II, Proceedings of SPIE, Kuo C.C.J., et al., eds., Vol. 3229, 1997, pp. 138–147.

123. Foote, J., Cooper, M., and Nam, U., Audio retrieval by rhythmic similarity, in Proceedings of the Third International Symposium on Musical Information Retrieval, Paris, September 2002.

124. Li, J.Z., Goralwalla, I.A., Özsu, M.T., and Szafron, D., Modeling video temporal relationships in an object database management system, Multimedia Comput. Networking, 80–91, 1997.

125. Gudivada, V.N., Raghavan, R., and Vanapipat, K., A Unified Approach to Data Modelling and Retrieval for a Class of Image Database Applications, Springer-Verlag, Heidelberg, 1996.

126. Park, Y., Kim, P., Golshani, F., and Panchanathan, S., Concept-based visual information management with large lexical corpus, in Proceedings of the International Conference on Database and Expert Applications (DEXA), Munich, September 2001. Springer-Verlag, Heidelberg, LNCS 2113, pp. 350–359.

127. Li, W.-S., Selçuk Candan, K., Hirata, K., and Hara, Y., Supporting efficient multimedia database exploration, VLDB J., 9, 312–326, 2001.

128. Brewer, E.A., When everything is searchable. Comm. ACM, 44, 53–54, 2001.

129. Aloia, N., Matera, M., and Paterno, F., Presentations for databases in multimedia environments. Multimedia Syst., 6, 408–420, 1998.

130. Baral, C., Gonzalez, G., and Nandigam, A., SQL+D: extended display capabilities for multimedia database queries, in ACM International Conference on Multimedia, Bristol, England, September 1998, pp. 109–114.

131. Marcus, S., Multimedia Database System: Issues and Research Direction, Springer-Verlag, Heidelberg, 1996.

132. Adiba, M. and Zechinelli-Martin, J.L., Spatio-temporal multimedia presentations as database objects, in International Conference on Database and Expert Systems Applications (DEXA), Florence, September 2000, Springer-Verlag, Heidelberg, LNCS Series 1677, pp. 974–985.

133. Adali, S., Sapino, M.L., and Subrahmanian, V.S., A multimedia presentation algebra, in Proceedings of the ACM SIGMOD International Conference of Management of Data, Philadelphia, June 1999, pp. 121–132.

134. Stonebraker, M., Object-Relational DBMS: The Next Wave, 2nd edition, Morgan Kaufmann, 1998.

135. Oria, V., Özsu, M.T., Xu, B., Cheng, L.I., and Iglinski, P., VisualMOQL: the DISIMA visual query language, in IEEE International Conference on Multimedia Computing and Systems, Florence, Italy, June 1999, Vol. 1, pp. 536–542.

136. Oria, V., Özsu, M.T., Iglinski, P., Lin, S., and Ya, B., DISIMA: a distributed and interoperable image database system, in Proceedings of the ACM SIGMOD International Conference of Management of Data, Dallas, May 2000, p. 600.

137. Freeman, R.G., Oracle 9i New Features, McGraw-Hill Osborne Media, 2002.

138. Chamberlain, D., A complete guide to DB2 Universal Database. Academic Press/Morgan Kaufmann, 1998.

139. Atnafu, S., Brunie, L., and Kosch, H., Similarity-based operators and query optimization for multimedia database systems, in Proceedings of the International Database Engineering and Applications Symposium (IDEAS), Grenoble, July 2001, IEEE CS Press, pp. 346–355.

140. Atnafu, S., Brunie, L., and Kosch, H., Similarity-based operators in image database systems, in Proceedings of the International Conference on Advances in Web-Age Information Management (WAIM), Xi'an, China, July 2001, Springer-Verlag, Heidelberg, LNCS 2118, pp. 14–25.

141. Kosch, H. and Atnafu, S., A multimedia join by the method of nearest neighbor search. Info. Processing Lett., 82, 269–276, 2002.

142. Leung, T.W., Mitchell, G., Subramanian, B., Vance, B., Vandenberg, S.L., and Zdonik, S.B., The Aqua data model and algebra. Technical Report CS-93-09, Brown University, Providence, 1993.

143. Cherniack, M. and Zdonik, S.B., Rule languages and internal algebrs for rule-based optimizers, in Proceedings of the ACM SIGMOD International Conference of Management of Data, Montréal, June 1996, pp. 401–412.

144. Cherniack, M. and Zdonik, S.B., Changing the rules: transformations for rule-based optimizers, in Proceedings of the ACM SIGMOD International Conference of Management of Data, Seattle, June 1998, pp. 61–72.

145. Hellerstein, J.M. and Stonebraker, M., Predicate migration: optimizing queries with expensive predicates, in Proceedings of the ACM SIGMOD International Conference of Managment of Data, Washington, DC, May 1993, pp. 256–257.

146. Chaudhuri, S. and Shim, K., Query optimization in the presence of foreign functions, in Proceedings of the International Conference on Very Large Databases, Dublin, 1993, pp. 529–542.

147. Scheufele, W. and Moerkotte, G., Efficient dynamic programming algorithms for ordering expensive joins and selections, in Proceedings of the International Conference on Extending Database Technology, Valencia, March 1998, pp. 23–27.

148. Adali, S., Bonatti, P., Sapino, M.L., and Subrahmanian, A.S., A multi-similarity algebra, in Proceedings of the ACM SIGMOD International Conference of Management of Data, Seattle, June 1998, ACM Press, pp. 402–413.

149. Ciaccia, P., Montesi, D., Penzo, W., and Trombetta, A., Imprecision and user preferences in multimedia queries: a generic algebraic approach, in Foundations of Information and Knowledge Systems, First International Symposium, Burg Spreewald, February 2000. Springer-Verlag, Heidelberg, LNCS 1762, pp. 50–71.

150. Nepal, S., Ramakrishna, M.V., and Thom, J.A., A fuzzy object query language (FOQL) for image databases, in International Conference on Database Systems for Advanced Applications, Hsinchu, April 1999. IEEE CS Press, pp. 117–124.

151. Nepal, S., Ramakrishna, M.V., and Thom, J.A., A fuzzy system for content based image retrieval, in Proceedings of the IEEE International Conference on Intelligent Processing Systems, Gold Coast, August 4–7, 1998, pp. 335–339.

152. Porkaew, K., Ortega, M., and Mehrotra, S., Query reformulation for content based multimedia retrieval in MARS, in IEEE International Conference on Multimedia Computing and Systems, Florence, June 1999, Vol. 2.

153. Chakrabarti, S., Porkaew, K., and Mehrotra, S., Efficient query refinement in multimedia databases, in Proceedings of the IEEE International Conference on Data Engineering (ICDE), San Diego, February–March 2000, p. 196.

154. Rui, Y., Huang, T., and Mehrotra, S., Relevance feedback: a powerful tool for contentbased image retrieval. IEEE Trans. Circuits Syst. Video Technol., 8, 25–36, 1998.

155. Phillips, B., Mediaway presses access to multimedia database. PC Week, 13, 39–40, 1996.

156. Khoshafian, S., Dasananda, S., and Minaasian, N., The Jasmine Object Database: Multimedia Applications for the Web, Morgan Kaufmann Publishers, 1998.

157. Woelk, D., Kim, W., and Luther, W., An object-oriented approach to multimedia databases, in SIGMOD Conf., Washington, D.C., 1986, pp. 311–325.

158. Stonebraker, M.R. and Rowe, L.A., The Design of POSTGRES, in Proceedings of the ACM SIGMOD International Conference on Management of Data, Washington, DC, May 1986, pp. 340–355.

159. de Vries, A.P., van Doorn, M.G.L.M., Blanken, H.M., and Apers, P.M.G., The MIRROR MMDBMS architecture, in Proceedings of the International Conference on Very Large Databases, Edinburgh, 1999, pp. 758–761.

160. van Doorn, M.G.L.M. and de Vries, A.P., The psychology of multimedia databases, in Proceedings of the Fifth ACM Conference on Digital Libraries, San Antonio, June 2000, pp. 1–9.

161. de Vries, A.P., Windhouwer, M.A., Apers, P.M.G., and Kersten, M.L., Information access in multimedia databases based on feature model, New Generation Comput., 18, 323–339, 2000.

162. Blok, H.E., Windhouwer, M.A., van Zwol, R., Petkovic, M., Apers, P.M.G., Kersten, M.L., and Jonker, W., Flexible and scalable digital library search, in Proceedings of the International Conference on Very Large Data Bases (VLDB), Rome, September 2001, pp. 705–706.

163. Rui, Y., Huang, T.S., and Mehrotra, S., MARS and its applications to MPEG-7. Technical Report TR-DB-97-05, Department of Computer Science, University of Illinois, Chicago, 1998.

164. Rui, Y., Huang, T.S., and Mehrotra, S., Constructing table-of-content for videos. ACM Multimedia Syst., 7, 359–368, 1999.

165. Chakrabarti, K. and Mehrotra, S. Efficient concurrency control in multidimensional access methods, in Proceedings of the International ACM SIGMOD Conference on Management of Data, Philadelphia, June 1999, pp. 25–36.

166. Döller, M., Kosch, H., Dörflinger, B., Bachlechner, A., and Blaschke, G., Demonstration of an MPEG-7 Multimedia Data Cartridge, ACM Multimedia 2002, Juan-Les-Pins, December 2002, pp. 429–430.

167. Döller, M. and Kosch, H., An MPEG-7 Multimedia Data Cartridge, SPIE Conference on Multimedia Computing and Networking 2003 (MMCN 2003), Santa Clara, January 2003.