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- W2053269318 abstract "A mixed autoregressive hidden Markov (MAR-HMM) is proposed for modeling people's movements. MAR-HMM is equivalent to a special case of an autoregressive hidden Markov model (AR-HMM), which takes into account changes of people's internal properties. The number of parameters is thus reduced in the case of MAR-HMM. A dataset is applied to evaluate MAR-HMM in this study. The prediction rate of MAR-HMM is 56.8% and that of AR-HMM is 51.5%. It is therefore concluded that MAR-HMM is applicable to trajectory analysis of pedestrians." @default.
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- W2053269318 date "2012-11-06" @default.
- W2053269318 modified "2023-10-03" @default.
- W2053269318 title "A mixed autoregressive hidden-markov-chain model applied to people's movements" @default.
- W2053269318 cites W1977555135 @default.
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- W2053269318 doi "https://doi.org/10.1145/2424321.2424378" @default.
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