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Intelligent Camera Control using Behavior Trees

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Uploaded on Sep 6, 2011

Daniel Markowitz, Joseph T. Kider Jr., Alexander Shoulson, and Norman I. Badler

Abstract:
Automatic camera systems produce very basic animations
for virtual worlds. Users often view environments through two types of
cameras: a camera that they control manually, or a very basic automatic
camera that follows their character, minimizing occlusions. Real cinematography
features much more variety producing more robust stories.
Cameras shoot establishing shots, close-ups, tracking shots, and bird's
eye views to enrich a narrative. Camera techniques such as zoom, focus,
and depth of field contribute to framing a particular shot. We present
an intelligent camera system that automatically positions, pans, tilts,
zooms, and tracks events occurring in real-time while obeying traditional
standards of cinematography. We design behavior trees that describe
how a single intelligent camera might behave from low-level narrative elements
assigned by "smart events". Camera actions are formed by hierarchically
arranging behavior sub-trees encapsulating nodes that control
specific camera semantics. This approach is more modular and particularly
reusable for quickly creating complex camera styles and transitions
rather then focusing only on visibility. Additionally, our user interface
allows a director to provide further camera instructions, such as prioritizing
one event over another, drawing a path for the camera to follow,
and adjusting camera settings on the fly. We demonstrate our method by
placing multiple intelligent cameras in a complicated world with several
events and storylines, and illustrate how to produce a well-shot "documentary"
of the events constructed in real-time.

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