×

A logical framework for visual information modeling and management. (English) Zbl 0986.68894

Summary: A unified semantic visual data-modeling framework is presented in the paper. In the proposed model, an extended conceptual graph is proposed as an annotation mechanism of a user’s perceptual understanding of video objects, activities, and events. A precise definition of the term “domain knowledge” in visual information processing is presented. A conceptual structure, associated terms, visual feature extraction methods, and a set of constraints in feature extraction are considered as domain information. The proposed visual data model has six different abstraction layers. A higher level is more abstracted and more semantically summarized. A polygon-based bounding volume is used in video object approximation in space and time. We use a bounding volume in motion trajectory representation, rather than motion vectors. This model allows simultaneous access of both temporal and spatial information. The proposed model may be used as a referencing framework for various visual information management systems’ developments.

MSC:

68U99 Computing methodologies and applications
68P20 Information storage and retrieval of data
68U10 Computing methodologies for image processing
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] S. Adali, K. S. Candan, S.-S. Chen, K. Erol, and V. S. Subrahmanian, Advanced video information system,ACM-Springer Multimedia Syst. J., 4, 172-186, August 1996 · doi:10.1007/s005300050021
[2] J. F. Allen, Maintaining knowledge about temporal intervals,Comm. ACM, 26(11), 832-843, 1983. · Zbl 0519.68079 · doi:10.1145/182.358434
[3] J. R. Bachet al. Virage image search engine: An open framework for image managemant,Proc. IS& T/SPIE?Storage and Retrieval for Still Image and Video Databases IV, 1996.
[4] D. S. Batory et al., GENESIS: An extensible database management system,IEEE Trans. Software Engrg., 14(11), 1171-1730, 1987.
[5] A. B. Benitez, M. Beigi, and S.-F. Chang, A content-based image meta-search engine using relevance feedback, http://www.ctr.columbia.edu/meta-seek.
[6] R. M. Bolle, B. L. Yeo, and M. M. Yeung, Video query: Research direction, http://www. almaden.ibm.com/journal/rd/422/bolle.txt.
[7] J. M. Careyet al., The architecture of EXODUS extensible DBMS, inACM International Workshop on Object-Oriented Database Systems, California, pp. 52-65, September 1986.
[8] Y.F. Day et al., A multi-level abstraction and modeling in video database,Multimedia Syst. 7, 409-423, 1999. · doi:10.1007/s005300050142
[9] N. Dimitrova and F. Golshani, Motion recovery for video content classification,ACM Trans. Office Inform. Syst., 13(4), 408-439, 1994. · doi:10.1145/211430.211433
[10] M. Egenhofer, Spatial SQL: A query and presentation language,IEEE Trans. Knowledge Data Engrg., 6(1), 86-95, 1994. · Zbl 05108739 · doi:10.1109/69.273029
[11] Excalibur System, http://www.excalibur.com/rev2/products/vrw/vrw.html.
[12] M. Flickner, Query by image and video content: The QBIC system,IEEE Comput. 28-9, 23-32, September 1994.
[13] F. Golshani, K. S. Candan, S. Panchnantan, and Y.C. Park, VIMOS: A video mosaic for spatiotemporal representation of visual information.IEEE Southwest Symposium on Image Analysis and Interpretation, Tucson AZ, 1998.
[14] F. Golshani and Y. C. Park, Content-based image indexing and retrievalin ImageRoadMap, Proc. SPIEs International Symposium on Voice, Video and Data Communications?Multimedia Storage and Archiving Systems II, Dallas, TX, pp. 194-204, November 1997.
[15] J. Griffioem, R. Mehrotra, and Y. Yavatkar, A semantic data model for embedded image information, inSecond International Conference on Information and Knowledge Management, Washington, D.C., pp. 393-402, November 1993.
[16] A. K. Jain and A. Vailaya, Image retrieval using color and shape,Pattern Recognition, 29, 1233-1244, August 1996. · Zbl 05475605 · doi:10.1016/0031-3203(95)00160-3
[17] J. Meng, Y. Juan, and S. F. Chang, Scene change detection in a MPED compressed video sequence, inIS& T/SPIE Symposium Proceedings, 2419, San Jose, CA, February 1994.
[18] R. Milaneseet al., Video segmentation and camera motion characterization using compressed data, inProc. SPIEs International Symposium on Voice, Video and Data Communications?Multimedia Storage and Archiving Systems II, Dallas, TX, pp. 79-91, November 1997.
[19] T. Minka, An image database browser that learns from user interaction, MIT Media Lab. Technical Report 364.
[20] MPEG Requirements Group, MPEG-7 Requirements Document, Doc. ISO/MPEG N2461, MPEG Atlantic City Meeting, October 1998.
[21] M. Nabil, J. Shepherd, and H. H. Ngu, 2D projection interval relationships: A symbolic representation of spatial relationships, inProceedings of 4th International Symposium on Large Spatial Database, Portland, Maine, ME, pp. 292-309, August 1995.
[22] M. Papadias, Y. Theodoridis, T. Selis, and M. J. Egenhofer, Topological relations in the world of minimum bounding rectangles: A study with R-tree, inProceedings of ACM SIGMOD International Conf. On Management of Data, San Jose, CA, USA, pp. 297-291, May 1995.
[23] Y. C. Park, Efficient tools for power annotation of visual contents: A lexicographical approach.ACM Multimedia 2000, Los Angeles.
[24] Y. Ruiet al., Content-based image retrieval with relevance feedback in MARS, inProc. IEEE Int. Conf. On Image Proc., 1997.
[25] J. R. Smith, VisualSEEK: A fully automated content-based image query system, ACM Multimedia Conference, Boston, MA, 1996.
[26] J. R. Smith, Integrated spatial and feature image systems: Retrieval, analysis and compression, Ph.D. dissertation, Department of Electrical Engineering, Columbia University, 1997.
[27] J. F. Sowa, Knowledge representation: Logical, philosophical, and computational foundations, PWS Publishing, Pacific Grove, CA, 1999.
[28] D. Swanberg, C. F. Shu, and R. Jain, Knowledge guided parsing in video databases,Image and Video Processing Conference, SPIE, 1908, 13-24, February 1993.
[29] H. Tamura and S. Moori, Textual features corresponding to visual perception,IEEE Trans. Systems Man Cybernet., 8(6) June 1978.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.