Browse > Article
http://dx.doi.org/10.9708/jksci.2011.16.7.067

A Semantic Annotation Method for Efficient Representation of Moving Objects  

Lee, Jin-Hwal (Dept. of Computer Information & Engineering, Inha University)
Hong, Myung-Duk (Dept. of Computer Information & Engineering, Inha University)
Lee, Kee-Sung (Dept. of Computer Information & Engineering, Inha University)
Jung, Jin-Guk (Dept. of Computer Information & Engineering, Inha University)
Jo, Geun-Sik (Dept. of Computer Information & Engineering, Inha University)
Abstract
Recently, researches for semantic annotation methods which represent and search objects included in video data, have been briskly activated since video starts to be popularized as types for interactive contents. Different location data occurs at each frame because coordinates of moving objects are changed with the course of time. Saving the location data for objects of every frame is too ineffective. Thus, it is needed to compress and represent effectively. This paper suggests two methods; the first, ontology modeling for moving objects to make users intuitively understandable for the information, the second, to reduce the amount of data for annotating moving objects by using cubic spline interpolation. To verify efficiency of the suggested method, we implemented the interactive video system and then compared with each video dataset based on sampling intervals. The result follows : when we got samples of coordinate less than every 15 frame, it showed that could save up to 80% amount of data storage; moreover, maximum of error deviation was under 31 pixels and the average was less than 4 pixels.
Keywords
Semantic Annotation; Ontology; Moving object; Spline interpolation; Video;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Y.J. Ji, H.J. Kim, and J.K. Heo, "Numerical Analysis with C Programming Language," NopiGipi, pp. 279-290, 2010.
2 J. Carmigniani, B. Furht, M. Anisetti, P. Ceravolo, E. Damiani, and M. Ivkovic, "Augmented reality technologies, systems and applications," Multimedia Tools and Applications, Vol. 51 pp. 341-377, 2011.   DOI   ScienceOn
3 S. You, and U. Neumann, "Mobile Augmented Reality for Enhancing E-Learning and E-Business," Internet Technology and Applications, International Conference on, pp. 1-4, Aug. 2010.
4 D.B. Goldman, C. Gonterman, B. Curless, D. Sale sin, and S.M. Seitz, "Video object annotation, navigation, and composition," In Proceedings of the 21st annual ACM symposium on User interface software and technology, ACM, pp. 3-12, 2008.
5 Y.A. Ahn, J.S, Park, and G.H, Ryu, "Location Prediction of Mobile Objects using the Cubic Spline Interpolation," KCC, Vol. 31, No. 5, pp. 479-491, 2004.
6 O. Wolfson, S. Chamberlain, Son Dao, Liqin Jiang, and G. Mendez, "Cost and imprecision in modeling the position of moving objects," Data Engineering, Proceedings, 14th International Conference on, pp. 588-596, Feb. 1998.
7 O. Wolfson, S. Chamberlain, and L. Jiang, "Moving objects databases: issues and solutions," Scientific and Statistical Database Management, Proceedings. Tenth International Conference on, pp. 111-122, Jul. 1998.
8 J.R. Cozar, N. Guil, J.M. Gonzalez-Linares, E.L.Za pata, and E. Izquierdo, "Logotype detection to support semantic-based video annotation," Signal Processing: Image Communication, Vol. 22, No. 7-8, pp. 669-679, Sep. 2007.   DOI   ScienceOn
9 A.R.J. Francois, R. Nevatia, J. Hobbs, R.C. Bolles, and J.R. Smith, "VERL: an ontology framework for representing and annotating video events," Multimedia, IEEE, Vol. 12, No. 4, pp. 76- 86, Oct.-Dec. 2005.   DOI   ScienceOn
10 V.S. Tseng, Su. Ja-Hwung, H. Jhih-Hong, and C. Chih-Jen, "Integrated Mining of Visual Features, Speech Features, and Frequent Patterns for Semantic Video Annotation," Multimedia, IEEE Transactions on , Vol. 10, No. 2, pp. 260-267, Feb. 2008.   DOI   ScienceOn
11 Y. Li, Y. Zhang, J. Lu, R. Lim, and J. Wang, "Video Analysis and Trajectory Based Video Annotation System," Wearable Computing Systems (APWCS), Asia-Pacific Conference on, pp. 307-310, April 2010.
12 M. Everingham, J. Sivic, and A. Zisserman, "Taking the bite out of automated naming of characters in TV video," The 17th British Machine Vision Conf. Image and Vision Computing, Vol. 27, pp. 545-559. April 2009.
13 W.C. Lee, Y.S. Moon, S.M. Lee, and H.Y. Noh, "Efficient Management of Moving Object Trajectories in the Stream Enviroment," KCC, pp. 166-170, 2006.
14 S.-B. Park, Y.W. Kim, and G.S. Jo, "Major Character Extraction using Character-Net," KSII, Vol. 11, No. 1, pp. 85-102, 2010.
15 L. Chen, G.C. Chen, C.Z. Xu, J. March, and S. Benford, "EmoPlayer: A media player for video clips with affective annotations," Interacting with Computers, Vol. 20, No. 1, pp. 17-28, Jan. 2008.   DOI   ScienceOn
16 J.H. Lee, S.-B. Park, Y.W. Kim, and G.S. Jo, "Automatic Video Annotation using Extraction of Character Name," KCC, Vol. 36, No. 1, pp. 525-530, 2009.