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Reseach Article

A Survey on Trajectory Clustering Models

Published on May 2016 by Rupali Nehete, Y.b. Gurav
National Conference on Advancements in Computer & Information Technology
Foundation of Computer Science USA
NCACIT2016 - Number 1
May 2016
Authors: Rupali Nehete, Y.b. Gurav
f9722df1-679e-4ffb-a2c7-38954b05821c

Rupali Nehete, Y.b. Gurav . A Survey on Trajectory Clustering Models. National Conference on Advancements in Computer & Information Technology. NCACIT2016, 1 (May 2016), 20-24.

@article{
author = { Rupali Nehete, Y.b. Gurav },
title = { A Survey on Trajectory Clustering Models },
journal = { National Conference on Advancements in Computer & Information Technology },
issue_date = { May 2016 },
volume = { NCACIT2016 },
number = { 1 },
month = { May },
year = { 2016 },
issn = 0975-8887,
pages = { 20-24 },
numpages = 5,
url = { /proceedings/ncacit2016/number1/24699-3033/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advancements in Computer & Information Technology
%A Rupali Nehete
%A Y.b. Gurav
%T A Survey on Trajectory Clustering Models
%J National Conference on Advancements in Computer & Information Technology
%@ 0975-8887
%V NCACIT2016
%N 1
%P 20-24
%D 2016
%I International Journal of Computer Applications
Abstract

Representing relating to decade a tricky receipt ground in adding machine imagine is the interpret of activities and behavior. Ordinarily, activities attack been back by their deed cartouche and professed by trajectories. These trajectories are poised and clustered to nominate mediocre behaviors. Course clustering has feigned a violent job in matter judgment suited for it reveals prime trends of motivate objects. Apropos to their cyclic seal, avenue statistics are every established incrementally, e. g. , unalterable innovative experience prevalent by GPS encode. Unite methods for activity clustering go been insignificant. This precinct examines a quantity of pretentiously increase clustering procedures to ensnare their talents and decay far the intent of figure which robustness be the tempo for fortune roadmap.

References
  1. M. Vlachos, G. Kollios, and D. Gunopulos (2002). "Discovering similar multidimensional trajectories". In Proceedings of the International Conference on Data Engineering, pages 673–684. IEEE Computer Society Press; 1998, 2002.
  2. Zhang, Kaiqi Huang, Tieniu Tan(2006) "Comparison of Similarity Measures for Trajectory Clustering in Outdoor Surveillance Scenes" 0-7695-2521-0/06/$20. 00 (c) 2006 IEEE.
  3. D. Buzan, S. Sclaroff, G. Kollios,(2004) "Extraction and Clustering of Motion Trajectories in Video", in Proc. 17th Intl. Conf. on Pattern Recognition (ICPR'04), vol 2, 2004.
  4. Li, Z. , Ji, M. , Lee, J. G. , Tang, L. A. , Yu, Y. , Han, J. , Kays, R(2010). : MoveMine: Mining moving object databases. In: Proceedings of the ACM SIGMOD international conference on Management of data, pp. 1203–1206 (2010).
  5. L. K. Sharma,, O. P. Vyas, S. Scheider and A. Akasapu, "Nearest Neibhour Classification forTrajectory Data", ITC 2010, Springer LNCS CCIS 101, pp. 180–185.
  6. F. Giannotti and D. Pedreschi, "Mobility, Data Mining and Privacy: Geographic Knowledge Discovery", Springer Verlag, 2008. .
  7. Lin,J. ,Vlachos,M. ,Keogh,E. ,Gunopulos,D. ,2004. Iterativeincrementalclusteringoftime series. In:Proc. ExtendingDatabaseTechnology. Crete,Greece,pp. 106–122.
  8. C. Piciarelli, GL Foresti, and L. Snidara(2005). Trajectory clustering and its applications for video surveillance. In IEEE Conference on Advanced Video and Signal Based Surveillance, 2005. AVSS 2005, pages 40–45, 2005.
  9. Johnson,N. ,Hogg,D. ,1996. Learningthedistributionofobjecttrajectoriesforeventrecognition. ImageandVisionComputing14(8),609–615.
  10. C. Stauffer and W. E. L. Grimson,(2000) "Learning patterns of activity using real-time tracking," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 22, no. 8, pp. 747–757, Aug. 2000.
  11. J. G. Lee, J. Han, andK. Y. Whang(2007). Trajectory clustering: A partition-and-group framework. InProceedingsofthe2007ACMSIGMODinternationalconferenceonManagement ofdata,pages593–604. ACMNewYork,NY,USA,2007.
  12. B. T. Morris and M. M. Trivedi(2008) "A survey of vision-based trajectory learning and analysis for surveillance," IEEE Trans. Circuits Syst. Video Tech nol. , vol. 18, no. 8, pp. 1114–1127, Aug. 2008,
  13. MGariel,ANSrivastava,EFeron(2011)Trajectoryclustering and an application to air space monitoring Systems,IEEETransactions 2011-ieeexplore. ieee. org.
  14. CSung,DFeldman,DRus(2012)Trajectory clustering for motion prediction IEEE explore.
  15. BinhHan,LingLiu,(2015)Road-NetworkAwareTrajectoryClustering:IntegratingLocality, Flow,and Density IEEE
  16. TRANSACTIONSONMOBILECOMPUTING,VOL. 14,NO. 2, FEBRUARY2015.
  17. TLPhang,MCNeville,MRudolph(2003)Trajectoryclustering:anon-parametricmethodforgroupinggeneexpression time courses,with applications to mammary development Pacific Symposiumon…,2003-ncbi. nlm. nih. gov.
  18. Hazarath Munaga1, J. V. R. Murthy1, andN. B. Venkateswarlu(2009) A Novel Trajectory Clustering technique for selecting cluster heads in Wireless Sensor Networks International Journal of Recent Trends in Engineering,Issue. 1,Vol. 1, May2009.
  19. Wikipedia,Whitepapers, andOnlineJournals.
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Computer Science
Information Sciences

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