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Combination of Multiple Measurement Cues for Visual Face Tracking

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Abstract

Visual face tracking is an important building block for all intelligent living and working spaces, as it is able to locate persons without any human intervention or the need for the users to carry sensors on themselves. In this paper we present a novel face tracking system built on a particle filtering framework that facilitates the use of non-linear visual measurements on the facial area. We concentrate on three different such non-linear visual measurement cues, namely object detection, foreground segmentation and colour matching. We derive robust measurement likelihoods under a unified representation scheme and fuse them into our face tracking algorithm. This algorithm is complemented with optimum selection of the particle filter’s object model and a target handling scheme. The resulting face tracking system is extensively evaluated and compared to baseline ones.

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Notes

  1. To obtain the sequence and the annotations contact the authors.

  2. See an example on http://www.youtube.com/watch?v=iI7mWvf0g1M.

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Authors and Affiliations

  1. Center for TeleInFrastruktur, Aalborg University, Fredrik Bajers Vej 7A, 9220 , Aalborg, Denmark

    Nikolaos Katsarakis, Zheng-Hua Tan & Ramjee Prasad

  2. Athens Information Technology, 0.8km Markopoulou Ave, 19002 , Peania, Athens, Greece

    Aristodemos Pnevmatikakis

Authors
  1. Nikolaos Katsarakis
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  2. Aristodemos Pnevmatikakis
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  3. Zheng-Hua Tan
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  4. Ramjee Prasad
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Corresponding author

Correspondence to Aristodemos Pnevmatikakis.

Additional information

Part of this work has been carried out in the scope of the EC co-funded projects SMART (FP7-287583) and eWALL (FP7-610658).

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Katsarakis, N., Pnevmatikakis, A., Tan, ZH. et al. Combination of Multiple Measurement Cues for Visual Face Tracking. Wireless Pers Commun 78, 1789–1810 (2014). https://doi.org/10.1007/s11277-014-1900-2

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  • DOI: https://doi.org/10.1007/s11277-014-1900-2

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