Person tracking using audio and depth cues

  title={Person tracking using audio and depth cues},
  • Published 2015
In this paper, a novel probabilistic Bayesian tracking scheme is proposed and applied to bimodal measurements consisting of tracking results from the depth sensor and audio recordings collected using binaural microphones. We use random finite sets to cope with varying number of tracking targets. A measurement-driven birth process is integrated to quickly localize any emerging person. A new bimodal fusion method that prioritizes the most confident modality is employed. The approach was tested on… CONTINUE READING


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Showing 1-10 of 24 references

A Survey on Human Motion Analysis from Depth Data

Time-of-Flight and Depth Imaging • 2013
View 1 Excerpt

Real-Time Human Pose Recognition in Parts from Single Depth Images

Machine Learning for Computer Vision • 2013
View 2 Excerpts

Tri-modal Person Re-identification with RGB, Depth and Thermal Features

2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops • 2013
View 1 Excerpt

Acoustic Source Localization and Tracking of a Time-Varying Number of Speakers

IEEE Transactions on Audio, Speech, and Language Processing • 2012
View 1 Excerpt

Adaptive Target Birth Intensity for PHD and CPHD Filters

IEEE Transactions on Aerospace and Electronic Systems • 2012
View 1 Excerpt

Face alignment through subspace constrained mean-shifts

2009 IEEE 12th International Conference on Computer Vision • 2009
View 1 Excerpt

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