Automated Camera Selection and Control for Better Training Support

نویسندگان

  • Adrian Ilie
  • Greg Welch
چکیده

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.

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تاریخ انتشار 2013