Automated Camera Selection and Control for Better Training Support

  • Adrian Ilie
  • Greg Welch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8027)


Physical training ranges have been shown to be critical in helping trainees integrate previously-perfected skills. There is a growing need for streamlining the feedback participants receive after training. This need is being met by two related research efforts: approaches for automated camera selection and control, and computer vision-based approaches for automated extraction of relevant training feedback information.

We introduce a framework for augmenting the capabilities present in training ranges that aims to help in both domains. Its main component is ASCENT (Automated Selection and Control for ENhanced Training), an automated camera selection and control approach for operators that also helps provide better training feedback to trainees.

We have tested our camera control approach in simulated and laboratory settings, and are pursuing opportunities to deploy it at training ranges. In this paper we outline the elements of our framework and discuss its application for better training support.


Planning Horizon Object Tracking Greedy Heuristic Camera Network Training Support 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Adrian Ilie
    • 1
  • Greg Welch
    • 2
  1. 1.The University of North Carolina at Chapel HillUSA
  2. 2.The University of Central FloridaUSA

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