DOI QR코드

DOI QR Code

Signature-based Indexing Scheme for Similar Sub-Trajectory Retrieval of Moving Objects

이동 객체의 유사 부분궤적 검색을 위한 시그니쳐-기반 색인 기법

  • 심춘보 (부산가톨릭대학교 컴퓨터정보공학부) ;
  • 장재우 (전북대학교 컴퓨터공학과)
  • Published : 2004.04.01

Abstract

Recently, there have been researches on storage and retrieval technique of moving objects, which are highly concerned by user in database application area such as video databases, spatio-temporal databases, and mobile databases. In this paper, we propose a new signature-based indexing scheme which supports similar sub-trajectory retrieval at well as good retrieval performance on moving objects trajectories. Our signature-based indexing scheme is classified into concatenated signature-based indexing scheme for similar sub-trajectory retrieval, entitled CISR scheme and superimposed signature-based indexing scheme for similar sub-trajectory retrieval, entitled SISR scheme according to generation method of trajectory signature based on trajectory data of moving object. Our indexing scheme can improve retrieval performance by reducing a large number of disk access on data file because it first scans all signatures and does filtering before accessing the data file. In addition, we can encourage retrieval efficiency by appling k-warping algorithm to measure the similarity between query trajectory and data trajectory. Final]y, we evaluate the performance on sequential scan method(SeqScan), CISR scheme, and SISR scheme in terms of data insertion time, retrieval time, and storage overhead. We show from our experimental results that both CISR scheme and SISR scheme are better than sequential scan in terms of retrieval performance and SISR scheme is especially superior to the CISR scheme.

최근 비디오 데이타베이스, 시공간 데이타베이스, 모바일 데이타베이스와 같은 데이타베이스 응용 분야에서 이동 객체를 기반으로 하는 검색 기법에 관한 연구가 활발히 이루어지고 있다. 본 논문에서는 이동 객체의 궤적에 대한 효율적인 유사 부분궤적 검색을 지원하는 새로운 시그니쳐-기반 색인 기법을 제안한다. 제안하는 시그니쳐-기반 색인 기법은 궤적 데이타를 토대로 궤적 시그니쳐를 생성하는 방법에 따라 중첩 시그니쳐-기반 색인 기법(Superimposed signature-based Indexing scheme for similar Sub-trajectory Retrieval : SISR)과 합성 시그니쳐-기반색인 기법(Concatenated signature-based Indexing scheme for similar Sub-trajectory Retrieval : CISR)으로 나뉜다. 생성된 궤적 시그니쳐 정보는 시그니쳐 파일에 저장되고, 검색시 주어진 사용자 질의 궤적 정보를 기반으로 데이타 파일을 직접 접근하기 전에 전체 궤적 시그니쳐들을 탐색하여 필터링을 수행한다. 이를 통해 데이타 파일의 검색 범위를 현저히 줄임으로써 검색 성능을 향상시킨다. 또한 검색된 궤적 데이터와의 유사성을 측정하기 위해 k-워핑 알고리즘을 적용시켜 검색의 효율성을 높인다. 마지막으로, 순차 색인 기법, SISR기법, 그리고 CISR 기법을 삽입시간, 검색 시간 그리고 부가 저장 공간측면에서 성능 평가를 수행한다. 성능 평가 결과, 제안하는 두 가지 기법이 검색 성능 측면에서 순차 색인 기법에 비해 성능이 우수함을 나타내고, 아울러 SISR 기법이 CISR 기법에 비해 보다 우수한 성능을 보인다.

Keywords

References

  1. W. Niblack, et al., 'The QBIC project : Quering by Iamge Content Using Color, Texture, and Shape,' in Procceedings of SPIE Storage and Retrieval for Image and Video Databases, pp. 173-187, 1993
  2. J. R. Smith, S. F. Chang, 'VisualSEEk : a Fully Automated Content-Based Image Query System,' in Procceedings of ACM Multimedia 96, pp.87-98, 1996 https://doi.org/10.1145/244130.244151
  3. T. D. C. Little, G. Ahanger, R. J. Folz, et al.,'A Digital On-Demand Video Service Supporting Content-Based Queries,' in Proceedings of ACM Multimedia '93, pp.427-436, 1993 https://doi.org/10.1145/166266.168450
  4. Virginia, E. Ogle and M. Stonebraker, 'Chabot: Retrieval from a Relational Database of images,' IEEE Computer, Vol.28, No.9, pp.40-48, 1995 https://doi.org/10.1109/2.410150
  5. A. Yoshitaka, M. Yoshimitsu, M. Hirakawa and T. Ichikawa, 'V-QBE : Video database retrieval by means of example motion of objects,' in Proceedings of IEEE International Conference on Multimedia Computing and Systems, pp.453-457, 1996 https://doi.org/10.1109/MMCS.1996.535013
  6. C. Faloutsos and S. Christodoulakis, 'Signature files : An access methods for documents and its anylytical performance evaluation,' ACM Transaction on Database Systems, Vol.2, No.4, pp.267-288, 1984 https://doi.org/10.1145/2275.357411
  7. C. C. Chang and J. H. Jiang, 'A fast spatial match retrieval using a superimposed coding technique,' In Proc. of the Int's Symposium on Advanced database Technologies and Their Integration, pp.71-78, 1994
  8. M. K. Shan and S. Y. Lee, 'Content-based Video Retrieval via Motion Trajectories,' In Proc. International Conference on SPIE Electronic Imaging and Multimedia System II, pp. 52-61, 1998
  9. J. Z. Li, M. T. Ozsu and D. Szafron, 'Modeling Video Temporal Relationships in an Object Database Management System,' In Proc. of Multimedia Computing and Networking(MMCN97), pp.80-91, 1997 https://doi.org/10.1117/12.264311
  10. M. Nabil, A. H. Ngu and J. Shepherd, 'Modeling Moving Objects in Multimedia Databases,' In Proc. of 5th International Conference on Database Systems for Advanced Applications, pp.67-76, 1997
  11. S. Dagtas, A. Ghafoor and R. L. Kashyap, 'Motion-based Indexing and Retrieval of Video using Object Trajectories,' In Proc. of 6th Workshop on Multimedia Information Systems, pp.33-41, 2000
  12. B. K. Yi, H. V. lagadish and C. Faloutsos, 'Efficient Retrieval of Similar Time Sequences Under Time Warping,' In Proc. International Conference on Data Engineering, pp. 201-208, 1998 https://doi.org/10.1109/ICDE.1998.655778
  13. S. H. Park, et al., 'Efficient Searches for Similar Subsequence of Difference Lengths in Sequence Databases,' In Proc. International Conference on Data Engineering, pp. 23-32, 2000
  14. S. W. Kim, S. H. Park and W. W. Chu, 'An Index-Based Approach for Similarity Search Supporting Time Warping in Large Sequence Databases,' In Proc. International Conference on Data Engineering, pp.607-614, 2001 https://doi.org/10.1109/ICDE.2001.914875
  15. G. Saltan, 'A New Comparison between Conventional Indexing(MEDLARS) and Automatic Text Processing (SMART),' Journal of the American Society for Information Science, Vol.23, No.2, pp.75-84, 1972 https://doi.org/10.1002/asi.4630230202
  16. G. Saltan and M. McGill, An introduction to Modern Information Retrieval, McGraw-Hill, 1993