MINDEX: An efficient index structure for salient-object-based queries in video databases

Abstract.Several salient-object-based data models have been proposed to model video data. However, none of them addresses the development of an index structure to efficiently handle salient-object-based queries. There are several indexing schemes that have been proposed for spatiotemporal relationships among objects, and they are used to optimize timestamp and interval queries, which are rarely used in video databases. Moreover, these index structures are designed without consideration of the granularity levels of constraints on salient objects and the characteristics of video data. In this paper, we propose a multilevel index structure (MINDEX) to efficiently handle the salient-object-based queries with different levels of constraints. We present experimental results showing the performance of different methods of MINDEX construction.

[1]  Lei Chen,et al.  A Multi-Level Index Structure for Video Databases , 2002, Multimedia Information Systems.

[2]  Yufei Tao,et al.  MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries , 2001, VLDB.

[3]  G L Hammond,et al.  Effect of burn injury on corticosteroid‐binding globulin levels in plasma and wound fluid , 1993, Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society.

[4]  Kotagiri Ramamohanarao,et al.  A two level superimposed coding scheme for partial match retrieval , 1983, Inf. Syst..

[5]  James F. Allen Maintaining knowledge about temporal intervals , 1983, CACM.

[6]  Venkat N. Gudivada,et al.  An algorithm for content-based retrieval in multimedia databases , 1996, Proceedings of the Third IEEE International Conference on Multimedia Computing and Systems.

[7]  G. Āllport The Psycho-Biology of Language. , 1936 .

[8]  Suh-Yin Lee,et al.  Retrieval of similar pictures on pictorial databases , 1991, Pattern Recognit..

[9]  Ahmed K. Elmagarmid,et al.  VideoText database systems , 1997, Proceedings of IEEE International Conference on Multimedia Computing and Systems.

[10]  Glorianna Davenport,et al.  The Stratification System - A Design Emvironment for Random Access , 1992, NOSSDAV.

[11]  Lei Chen,et al.  Modeling Video Data for Content Based Queries: Extending the DISIMA Image Data Model , 2003, MMM.

[12]  Anne H. H. Ngu,et al.  Modelling Moving Objects in Multimedia Databases , 1997, DASFAA.

[13]  G. Zipf,et al.  The Psycho-Biology of Language , 1936 .

[14]  Christos Faloutsos,et al.  QBIC project: querying images by content, using color, texture, and shape , 1993, Electronic Imaging.

[15]  Duane Szafron,et al.  Modeling of moving objects in a video database , 1997, Proceedings of IEEE International Conference on Multimedia Computing and Systems.

[16]  Timos K. Sellis,et al.  Specifications for efficient indexing in spatiotemporal databases , 1998, Proceedings. Tenth International Conference on Scientific and Statistical Database Management (Cat. No.98TB100243).

[17]  SUH-YIN LEE,et al.  Access Methods of Image Database , 1990, Int. J. Pattern Recognit. Artif. Intell..

[18]  Timos K. Sellis,et al.  Spatio-temporal composition and indexing for large multimedia applications , 1998, Multimedia Systems.

[19]  Christos Faloutsos,et al.  Signature files: an access method for documents and its analytical performance evaluation , 1984, TOIS.

[20]  Glorianna Davenport,et al.  The Stratification System A Design Environment for Random Access Video , 2005 .

[21]  Shi-Kuo Chang,et al.  Iconic Indexing by 2-D Strings , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Atreyi Kankanhalli,et al.  Automatic partitioning of full-motion video , 1993, Multimedia Systems.

[23]  D. Arijon,et al.  Grammar of Film Language , 1976 .

[24]  Stephen W. Smoliar,et al.  Video parsing, retrieval and browsing: an integrated and content-based solution , 1997, MULTIMEDIA '95.

[25]  Bernhard Seeger,et al.  An asymptotically optimal multiversion B-tree , 1996, The VLDB Journal.

[26]  Arbee L. P. Chen,et al.  Content-Based Query Processing for Video Databases , 2000, IEEE Trans. Multim..

[27]  Wei-Pang Yang,et al.  Efficient Image Retrieval Algorithms for Large Spatial Databases , 1994, Int. J. Pattern Recognit. Artif. Intell..

[28]  Curtis R. Cook,et al.  A letter oriented minimal perfect hashing function , 1982, SIGP.

[29]  Justin Zobel,et al.  Performance in Practice of String Hashing Functions , 1997, DASFAA.

[30]  Mario A. Nascimento,et al.  Towards historical R-trees , 1998, SAC '98.

[31]  Essam A. El-Kwae,et al.  Efficient content-based indexing of large image databases , 2000, TOIS.

[32]  Dik Lun Lee,et al.  Efficient Signature File Methods for Text Retrieval , 1995, IEEE Trans. Knowl. Data Eng..

[33]  Özgür Ulusoy,et al.  A rule-based video database system architecture , 2002, Inf. Sci..

[34]  Lei Chen,et al.  Modeling of video objects in a video databases , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.