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3D Tracking and Classification System Using a Monocular Camera

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Abstract

This paper details a 3D tracking and recognition system using a single camera. The system is able to track and classify targets in outdoors and indoors scenarios, as long as they move (at least approximately) on a plane. The system first detects and validates targets and then tracks them in a state-space employing cylindrical models (horizontal and vertical position on the ground, their radius and height) utilising Particle Filters. The tracker fuses visual measurements that utilise the targets’ foreground and colour models. Finally the system classifies the tracked objects based on the visual metrics extracted by our algorithm. We have tested our model in an outdoor setting using humans and automobiles passing through the field of view of the camera at various speeds and distances. The results presented in this paper show the validity our approach.

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Authors and Affiliations

  1. Athens Information Technology, Multimodal Signal Analytics, 44, Kifisias Ave., 15125, Marousi, Athens, Greece

    George Bardas, Stefanos Astaras, Sotirios Diamantas & Aristodemos Pnevmatikakis

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  1. George Bardas
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  2. Stefanos Astaras
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  3. Sotirios Diamantas
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  4. Aristodemos Pnevmatikakis
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Correspondence to Aristodemos Pnevmatikakis.

Additional information

Part of this work has been carried out in the scope of the EC co-funded projects ARGOS (FP7-SEC-2012-1) and eWALL (FP7-610658).

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Bardas, G., Astaras, S., Diamantas, S. et al. 3D Tracking and Classification System Using a Monocular Camera. Wireless Pers Commun 92, 63–85 (2017). https://doi.org/10.1007/s11277-016-3839-y

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