Real-Time Tracking of Single and Multiple Objects from Depth-Colour Imagery Using 3D Signed Distance Functions |
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Authors: | C Y Ren V A Prisacariu O Kähler I D Reid D W Murray |
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Affiliation: | 1.Department of Engineering Science,University of Oxford,Oxford,UK;2.School of Computer Science,University of Adelaide,Adelaide,Australia |
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Abstract: | We describe a novel probabilistic framework for real-time tracking of multiple objects from combined depth-colour imagery. Object shape is represented implicitly using 3D signed distance functions. Probabilistic generative models based on these functions are developed to account for the observed RGB-D imagery, and tracking is posed as a maximum a posteriori problem. We present first a method suited to tracking a single rigid 3D object, and then generalise this to multiple objects by combining distance functions into a shape union in the frame of the camera. This second model accounts for similarity and proximity between objects, and leads to robust real-time tracking without recourse to bolt-on or ad-hoc collision detection. |
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