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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

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Chicago
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.
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.
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.
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.
@article{4361272,
  author       = {Chavoshi, Seyed Hossein and De Baets, Bernard and Neutens, Tijs and Ban, Hyowon and Ahlqvist, Ola and De Tr{\'e}, Guy and Van de Weghe, Nico},
  issn         = {0143-6228},
  journal      = {APPLIED GEOGRAPHY},
  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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