A Layered Hidden Markov Model for predicting human trajectories in a multi-floor building

• Main Authors: LI, Qian, LAU, Hoong Chuin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Layered Hidden Markov Model (LHMM); trajectory sensing; trajectory modelling; mobility recognition; Artificial Intelligence and Robotics; Computer Sciences; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/2911; https://ink.library.smu.edu.sg/context/sis_research/article/3911/viewcontent/Layer_Hidden_Markov_2015_pv.pdf
• Institution: Singapore Management University

Tracking and modeling huge amount of users’ movement in a multi-floor building by using wireless devices is a challenging task, due to crowd movement complexity and signal sensing accuracy. In this paper, we use Layered Hidden Markov Model (LHMM) to fit the spatial-temporal trajectories (with large...