Reconstructing Pedestrian Trajectories from Partial Observations in the Urban Context

  • Ricardo Miguel Puma AlvarezEmail author
  • Alneu de Andrade Lopes
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 795)


The ever-greater number of technologies providing location-based services has given rise to a deluge of trajectory data. However, most of these trajectories are low-sampling-rate and, consequently, many movement details are lost. Due to that, trajectory reconstruction techniques aim to infer the missing movement details and reduce uncertainty. Nevertheless, most of the effort has been put into reconstructing vehicle trajectories. Here, we study the reconstruction of pedestrian trajectories by using road network information. We compare a simple technique that only uses road network information with a more complex technique that, besides the road network, uses historical trajectory data. Additionally, we use three different trajectory segmentation settings to analyze their influence over reconstruction. Our experiment results show that, with the limited pedestrian trajectory data available, a simple technique that does not use historical data performs considerably better than a more complex technique that does use it. Furthermore, our results also show that trajectories segmented in such a way as to allow a greater distance and time span between border points of pairs of consecutive trajectories obtain better reconstruction results in the majority of the cases, regardless of the technique used.



This work was supported by FAPESP grant 2015/14228-9, CNPq grants 302645/2015-2, 162262/2014-0 and CAPES grant PROEX-9152559/M.


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Ricardo Miguel Puma Alvarez
    • 1
    Email author
  • Alneu de Andrade Lopes
    • 1
  1. 1.Instituto de Ciências Matemáticas e de ComputaçãoUniversidade de São Paulo - Campus de São CarlosSão CarlosBrazil

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