Journals Information
Computer Science and Information Technology Vol. 3(4), pp. 138 - 147
DOI: 10.13189/csit.2015.030408
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Classification of Trajectories Using Category Maps and U-Matrix to Predict Interests Used for Event Sites
Hirokazu Madokoro *, Kazuhito Sato , Nobuhiro Shimoi
Faculty of Systems Science and Technology, Akita Prefectural University, 84--4, Tsuchiya Aza Ebinokuchi, Yurihonjo City, Akita, 015--0055, Japan
ABSTRACT
This paper presents a method for classification and recognition of behavior patterns based on interest from human trajectories at an event site. Our method creates models using Hidden Markov Models (HMMs) for each human trajectory quantized using One-Dimensional Self-Organizing Maps (1D-SOMs). Subsequently, we apply Two-Dimensional SOMs (2D-SOMs) for unsupervised classification of behavior patterns from features according to the distance between models. Furthermore, we use a Unified distance Matrix (U-Matrix) for visualizing category boundaries based on the Euclidean distance between weights of 2D-SOMs. Our method extracts typical behavior patterns and specific behavior patterns based on interest as ascertained using questionnaires. Then our method visualizes relations between these patterns. We evaluated our method based on Cross Validation (CV) using only the trajectories of typical behavior patterns. The recognition accuracy improved 9.6% over that of earlier models. We regard our method as useful to estimate interest from behavior patterns at an event site.
KEYWORDS
Trajectory Analysis, Self-Organizing Maps, Hidden Markov Models, U-Matrix, Cross Validation
Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Hirokazu Madokoro , Kazuhito Sato , Nobuhiro Shimoi , "Classification of Trajectories Using Category Maps and U-Matrix to Predict Interests Used for Event Sites," Computer Science and Information Technology, Vol. 3, No. 4, pp. 138 - 147, 2015. DOI: 10.13189/csit.2015.030408.
(b). APA Format:
Hirokazu Madokoro , Kazuhito Sato , Nobuhiro Shimoi (2015). Classification of Trajectories Using Category Maps and U-Matrix to Predict Interests Used for Event Sites. Computer Science and Information Technology, 3(4), 138 - 147. DOI: 10.13189/csit.2015.030408.