Evaluation of Trajectory Clustering Based on Information Criteria for Human Activity Analysis

Asahara, Akinori; Sato, Akiko; Maruyama, Kishiko

doi:10.1109/mdm.2009.65

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Related Work 21 Discrete and Continuous Positioning1

Conventional Probabilistic Models1

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2011

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(2 citation statements)

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“…Trajectory analysis is a technique for extracting abstract information from a stored trajectory [1]. A "trajectory" of a pedestrian is the path on which he or she moves, which is described as a continuous function of time x = x(t).…”

Section: Related Work 21 Discrete and Continuous Positioningmentioning

confidence: 99%

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Pedestrian-movement prediction based on mixed Markov-chain model

Asahara

Maruyama

Sato

et al. 2011

Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

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163

125

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A method for predicting pedestrian movement on the basis of a mixed Markov-chain model (MMM) is proposed. MMM takes into account a pedestrian's personality as an unobservable parameter. It also takes into account the eects of the pedestrian's previous status. A promotional experiment in a major shopping mall demonstrated that the highest prediction accuracy of the MMM method is 74.4%. In comparison with methods based on a Markov-chain model (MM) and a hidden-Markov model (HMM) (i.e., prediction rates of about 45% and 2%, respectively), the proposed MMM-based prediction method is substantially more accurate. This pedestrian-movement prediction based on MMM using tracking data will make it possible to provide so-called "adaptive mobile services" with proactive functions.

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Section: Related Work 21 Discrete and Continuous Positioningmentioning

confidence: 99%

“…A transition probability from state μ to state ν is thus a constant denoted as ωμν , where ν ωμν = 1. The overall transition probability is therefore written as (1) and the ωμν is estimated by following formula:…”

Section: Conventional Probabilistic Modelsmentioning

confidence: 99%

Pedestrian-movement prediction based on mixed Markov-chain model

Asahara

Maruyama

Sato

et al. 2011

Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Evaluation of Trajectory Clustering Based on Information Criteria for Human Activity Analysis

Cited by 1 publication

References 10 publications

Pedestrian-movement prediction based on mixed Markov-chain model

Pedestrian-movement prediction based on mixed Markov-chain model

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