Vision and RFID data fusion for tracking people in crowds by a mobile robot

  • Authors:
  • T. Germa;F. Lerasle;N. Ouadah;V. Cadenat

  • Affiliations:
  • CNRS, LAAS, 7, Avenue du Colonel Roche, F-31077 Toulouse, France and Université de Toulouse, UPS, INSA, INP, ISAE, LAAS-CNRS, F-31077 Toulouse, France;CNRS, LAAS, 7, Avenue du Colonel Roche, F-31077 Toulouse, France and Université de Toulouse, UPS, INSA, INP, ISAE, LAAS-CNRS, F-31077 Toulouse, France;CNRS, LAAS, 7, Avenue du Colonel Roche, F-31077 Toulouse, France and CDTA/ENP, Cité 20 aoít 1956, Baba Hassen, Alger, Algeria;CNRS, LAAS, 7, Avenue du Colonel Roche, F-31077 Toulouse, France and Université de Toulouse, UPS, INSA, INP, ISAE, LAAS-CNRS, F-31077 Toulouse, France

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2010

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Abstract

In this paper, we address the problem of realizing a human following task in a crowded environment. We consider an active perception system, consisting of a camera mounted on a pan-tilt unit and a 360^o RFID detection system, both embedded on a mobile robot. To perform such a task, it is necessary to efficiently track humans in crowds. In a first step, we have dealt with this problem using the particle filtering framework because it enables the fusion of heterogeneous data, which improves the tracking robustness. In a second step, we have considered the problem of controlling the robot motion to make the robot follow the person of interest. To this aim, we have designed a multi-sensor-based control strategy based on the tracker outputs and on the RFID data. Finally, we have implemented the tracker and the control strategy on our robot. The obtained experimental results highlight the relevance of the developed perceptual functions. Possible extensions of this work are discussed at the end of the article.