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Knowledge discovery in choreographic data using Relative Motion matrices and Dynamic Time Warping

(2014) APPLIED GEOGRAPHY. 47. p.111-124
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Keywords
Similarity analysis, EVENTS, DTW, REMO, Moving point object, Motion pattern, SERIES, PATTERNS, RECOGNITION, BLUETOOTH

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Citation

Please use this url to cite or link to this publication:

MLA
Chavoshi, Seyed Hossein, Bernard De Baets, Tijs Neutens, et al. “Knowledge Discovery in Choreographic Data Using Relative Motion Matrices and Dynamic Time Warping.” APPLIED GEOGRAPHY 47 (2014): 111–124. Print.
APA
Chavoshi, S. H., De Baets, B., Neutens, T., Ban, H., Ahlqvist, O., De Tré, G., & Van de Weghe, N. (2014). Knowledge discovery in choreographic data using Relative Motion matrices and Dynamic Time Warping. APPLIED GEOGRAPHY, 47, 111–124.
Chicago author-date
Chavoshi, Seyed Hossein, Bernard De Baets, Tijs Neutens, Hyowon Ban, Ola Ahlqvist, Guy De Tré, and Nico Van de Weghe. 2014. “Knowledge Discovery in Choreographic Data Using Relative Motion Matrices and Dynamic Time Warping.” Applied Geography 47: 111–124.
Chicago author-date (all authors)
Chavoshi, Seyed Hossein, Bernard De Baets, Tijs Neutens, Hyowon Ban, Ola Ahlqvist, Guy De Tré, and Nico Van de Weghe. 2014. “Knowledge Discovery in Choreographic Data Using Relative Motion Matrices and Dynamic Time Warping.” Applied Geography 47: 111–124.
Vancouver
1.
Chavoshi SH, De Baets B, Neutens T, Ban H, Ahlqvist O, De Tré G, et al. Knowledge discovery in choreographic data using Relative Motion matrices and Dynamic Time Warping. APPLIED GEOGRAPHY. 2014;47:111–24.
IEEE
[1]
S. H. Chavoshi et al., “Knowledge discovery in choreographic data using Relative Motion matrices and Dynamic Time Warping,” APPLIED GEOGRAPHY, vol. 47, pp. 111–124, 2014.
@article{4361272,
  author       = {Chavoshi, Seyed Hossein and De Baets, Bernard and Neutens, Tijs and Ban, Hyowon and Ahlqvist, Ola and De Tré, Guy and Van de Weghe, Nico},
  issn         = {0143-6228},
  journal      = {APPLIED GEOGRAPHY},
  keywords     = {Similarity analysis,EVENTS,DTW,REMO,Moving point object,Motion pattern,SERIES,PATTERNS,RECOGNITION,BLUETOOTH},
  language     = {eng},
  pages        = {111--124},
  title        = {Knowledge discovery in choreographic data using Relative Motion matrices and Dynamic Time Warping},
  url          = {http://dx.doi.org/10.1016/j.apgeog.2013.12.007},
  volume       = {47},
  year         = {2014},
}

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