Machine Vision and Applications

, Volume 25, Issue 4, pp 901–917 | Cite as

OPTIMUS:online persistent tracking and identification of many users for smart spaces

Original Paper

Abstract

A smart space, which is embedded with networked sensors and smart devices, can provide various useful services to its users. For the success of a smart space, the problem of tracking and identification of smart space users is of paramount importance. We propose a system, called Optimus, for persistent tracking and identification of users in a smart space, which is equipped with a camera network. We assume that each user carries a smartphone in a smart space. A camera network is used to solve the problem of tracking multiple users in a smart space and information from smartphones is used to identify tracks. For robust tracking, we first detect human subjects from images using a head detection algorithm based on histograms of oriented gradients. Then, human detections are combined to form tracklets and delayed track-level association is used to combine tracklets to build longer trajectories of users. Last, accelerometers in smartphones are used to disambiguate identities of trajectories. By linking identified trajectories, we show that the average length of a track can be lengthened by over six times. The performance of the proposed system is evaluated extensively in realistic scenarios.

Keywords

Tracking Identification Smart space Smartphone Camera network 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.CPSLAB, ASRI, School of Electrical Engineering and Computer Science Seoul National UniversitySeoulKorea

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